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duxiu/initial_release/40035780.zip

智能处理技术 1997年IEEE智能处理系统国际会议论文集上、下清华大学计算机系编, IEEE International Conference on Intelligent Processing Systems, International conference, 1st 万国学术出版社, 1997, 1997

These proceedings are intended for manufacturing process control engineers; computer networking engineers; and computer software engineers.

英语 [en] · 中文 [zh] · PDF · 183.0MB · 1997 · 📗 未知类型的图书 · 🚀/duxiu/zlibzh · Save

ia/methodologiesfor0001inte.pdf

Methodologies For The Conception, Design, And Application Of Intelligent Systems - Proceedings Of The 4th International Conference On Soft Computing (In 2 Volumes) Gen Matsumoto; Takeshi Yamakawa; International Fuzzy Systems Association; International Conference on Soft Computing World Scientific Publishing Comp, World Scientific Publishing Company, Singapore, 1996

IIZUKA'96, the 4th International Conference on Soft Computing, emphasized the integration of the components of soft computing to promote the research work on post-digital computers and to realize the intelligent systems. At the conference, new developments and results in soft computing were introduced and discussed by researchers from academic, governmental, and industrial institutions.This volume presents the opening lectures by Prof. Lotfi A. Zadeh and Prof. Walter J. Freeman, the plenary lectures by seven eminent researchers, and about 200 carefully selected papers drawn from more than 20 countries. It documents current research and in-depth studies on the conception, design, and application of intelligent systems.

英语 [en] · 中文 [zh] · PDF · 42.4MB · 1996 · 📗 未知类型的图书 · 🚀/ia · Save

ia/isbn_9789810244613.pdf

Advanced signal processing technology by soft computing. Vol. 1 Hsu, Charles World Scientific Publishing Company, World Scientific Publishing Company, Singapore, 2001

This book presents worldwide outstanding research and recent progress in the applications of neural networks, fuzzy logic, chaos, independent component analysis, etc to fields related to speech recognition enhancement, supervised Fourier demixing noise elimination, acoustic databases, the human hearing system, cancer detection, image processing, and visual communications.

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ia/proceedingsofint0000inte_f1w0.pdf

Proceedings of the International Workshop on Soft computing in remote sensing data analysis : proceedings of the international workshop, Milan, Italy Dec. 4-5, 1995 International Workshop on Soft Computing in Remote Sensing Data Analysis (1995: Milan, Italy); Binaghi, Elisabetta; Brivio, Pietro Alessandro; Rampini, Anna World Scientific Publishing Company, Series in remote sensing ;, vol. 1, Singapore, River Edge, NJ, Singapore, 1996

xi, 260 p. : 23 cm Includes bibliographical references

英语 [en] · PDF · 15.3MB · 1996 · 📗 未知类型的图书 · 🚀/ia · Save

ia/neurofuzzysoftco0000jang.pdf

Neuro-fuzzy and soft computing : a computational approach to learning and machine intelligence Jang, Jyh-Shing Roger, Sun, Chuen-Tsai, Mizutani, Eiji MATLAB CURRICULUM SERIES, MATLAB curriculum series, Upper Saddle River, NJ, New Jersey, 1997

neuro-fuzzy Modeling And Soft Computing Places Particular Emphasis On The Theoretical Aspects Of Covered Methodologies, As Well As Empirical Observations And Verifications Of Various Applications In Practice.neuro-fuzzy Modeling And Soft Computing Is Oriented Toward Methodologies That Are Likely To Be Of Practical Use. It Includes Exercises, Some Of Which Involve Matlab Programming Tasks To Provide Readers With Hands-on Programming Experiences For Practical Problem-solving. Each Chapter Also Includes A Reference List To The Research Literature So That Readers May Pursue Topics In Greater Depth.this Book Is Suitable As A Self-study Guide By Researchers Who Want To Learn Basic And Advanced Neuro-fuzzy And Soft Computing Within The Framework Of Computational Intelligence. <h3>booknews</h3> unlike Traditional, Hard Computing, This Field Aims To Accommodate The Pervasive Imprecision Of The Real World, Using The Human Mind As Its Role Model. Intended For Use As A Graduate Level Text, Or A Self- Study Guide For Students And Researchers, This Book Presents An Introduction To The Field, And Then Covers Fuzzy Set Theory, Regression And Optimization, Neutral Networks, Neuro-fuzzy Modeling And Controls, And Advanced Applications. It Also Includes Hints To Selected Exercises, And Lists Of Internet Resources, Matlab Programs, And Acronyms. Contains An Offer For Free Companion Software. Annotation C. Book News, Inc., Portland, Or (booknews.com)

英语 [en] · PDF · 33.9MB · 1997 · 📗 未知类型的图书 · 🚀/duxiu/ia · Save

lgli/V:\!GST\DVD 20 - Great Science Textbooks DVD Library 2007 - Update Jul 2009\Computer Science\Artificial Intelligence\Rutkowski - Computational Intelligence - Methods and Techniques (2005).pdf

Computational Intelligence - Methods and Techniques Leszek Rutkowski Springer Berlin / Heidelberg, 1st Edition., 2010

This quite simply superb book focuses on various techniques of computational intelligence, both single ones and those which form hybrid methods. These techniques are today commonly applied to issues of artificial intelligence. The book presents methods of knowledge representation using different techniques, namely the rough sets, type-1 fuzzy sets and type-2 fuzzy sets. Next up, various neural network architectures are presented and their learning algorithms are derived. Then, the family of evolutionary algorithms is discussed, including connections between these techniques and neural networks and fuzzy systems. Finally, various methods of data partitioning and algorithms of automatic data clustering are given and new neuro-fuzzy architectures are studied and compared.

英语 [en] · PDF · 18.1MB · 2010 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save

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Advances in Fuzzy Clustering and its Applications José Valente de Oliveira; Witold Pedrycz Wiley & Sons, Limited, John, June 15, 2007

A comprehensive, coherent, and in depth presentation of the state of the art in fuzzy clustering . Fuzzy clustering is now a mature and vibrant area of research with highly innovative advanced applications. Encapsulating this through presenting a careful selection of research contributions, this book addresses timely and relevant concepts and methods, whilst identifying major challenges and recent developments in the area. Split into five clear sections, Fundamentals, Visualization, Algorithms and Computational Aspects, Real-Time and Dynamic Clustering, and Applications and Case Studies, the book covers a wealth of novel, original and fully updated material, and in particular offers: a focus on the algorithmic and computational augmentations of fuzzy clustering and its effectiveness in handling high dimensional problems, distributed problem solving and uncertainty management. presentations of the important and relevant phases of cluster design, including the role of information granules, fuzzy sets in the realization of human-centricity facet of data analysis, as well as system modelling demonstrations of how the results facilitate further detailed development of models, and enhance interpretation aspects a carefully organized illustrative series of applications and case studies in which fuzzy clustering plays a pivotal role This book will be of key interest to engineers associated with fuzzy control, bioinformatics, data mining, image processing, and pattern recognition, while computer engineers, students and researchers, in most engineering disciplines, will find this an invaluable resource and research tool.

英语 [en] · PDF · 9.0MB · 2007 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save

ia/isbn_9789810245177.pdf

New Paradigm Of Knowledge Engineering By Soft Computing, A Liya Ding; Fuzzy Logic Systems Institute; International Conference on Soft Computing World Scientific Publishing Company, Incorporated, World Scientific Publishing Company, Singapore, 2001

Annotation. Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms. The integration of those constituent methodologies forms the core of SC. In addition, the synergy allows SC to incorporate human knowledge effectively, deal with imprecision and uncertainty, and learn to adapt to unknown or changing environments for better performance. Together with other modern technologies, SC and its applications exert unprecedented influence on intelligent systems that mimic human intelligence in thinking, learning, reasoning, and many other aspects. Knowledge engineering (KE), which deals with knowledge acquisition, representation, validation, inferencing, explanation, and maintenance, has made significant progress recently, owing to the indefatigable efforts of researchers. Undoubtedly, the hot topics of data mining and knowledge/data discovery have injected new life into the classical AI, world. This book tells readers how KE has been influenced and extended by SC and how SC will be helpful in pushing the frontier of KE further. It is intended for researchers and graduate students to use as a reference in the study of knowledge engineering and intelligent systems. The reader is expected to have a basic knowledge of fuzzy logic, neural networks, genetic algorithms, and knowledge-based systems

英语 [en] · PDF · 15.2MB · 2001 · 📗 未知类型的图书 · 🚀/duxiu/ia · Save

ia/isbn_9783790812497.pdf

This volume prepared by Roman Slowinski and Maciej Hapke is welcome because it is representative of the current state of the art in fuzzy set-based scheduling. Its publication proves that some operational research scientists start to consider fuzzy sets seriously as a bridge for a reconciliation between mathematical modeling and human scheduling practice. A difficulty for the reader of the fuzzy set scheduling literature is to understand the precise role of fuzzy sets in the various published papers. More often than not, the meaning of fuzzy sets remain unclear or must be guessed from the context of the problem. A major contribution of this volume is to try and clarify this issue through a suitable ordering of the papers, telling apart those where fuzzy sets is mainly a matter of representing preference, and those where the problem is one of scheduling under uncertainty. Taken from the foreword by Didier Dubois and Henry Prade

英语 [en] · PDF · 16.0MB · 2000 · 📗 未知类型的图书 · 🚀/ia · Save

upload/misc/Y9EgLx762wKqWqG7nloH/Books/Gentoomen Library/Artificial Intelligence/Fuzzy systems/Neuro-Fuzzy and Soft Computing A Computational Approach to Learning and Machine Intelligence - Jyh-Shing Roger Jang.djvu

Neuro-fuzzy and soft computing : a computational approach to learning and machine intelligence Jyh-Shing Roger Jang, Chuen-Tsai Sun, Eiji Mizutani Prentice Hall, MATLAB curriculum series, Upper Saddle River, NJ, New Jersey, 1997

Neuro-Fuzzy and Soft Computing provides the first comprehensive treatment of the constituent methodologies underlying neuro-fuzzy and soft computing, an evolving branch of computational intelligence. The constituent methodologies include fuzzy set theory, neural networks, data clustering techniques, and several stochastic optimization methods that do not require gradient information. In particular, the authors put equal emphasis on theoretical aspects of covered methodologies, as well as empirical observations and verifications of various applications in practice. The book is well suited for use as a text for courses on computational intelligence and as a single reference source for this emerging field. To help readers understand the material the presentation includes more than 50 examples, more than 150 exercises, over 300 illustrations, and more than 150 Matlab scripts. In addition, Matlab is utilized to visualize the processes of fuzzy reasoning, neural-network learning, neuro-fuzzy integration and training, and gradient-free optimization (such as genetic algorithms, simulated annealing, random search, and downhill Simplex method). The presentation also makes use of SIMULINK for neuro-fuzzy control system simulations. All Matlab scripts used in the book are available on the free companion software disk that may be ordered by using the enclosed reply card. The book also contains an "Internet Resource Page" to point the reader to on-line neuro-fuzzy and soft computing home pages, publications, public-domain software, research institutes, news groups, etc.

英语 [en] · DJVU · 7.3MB · 1997 · 📘 非小说类图书 · 🚀/duxiu/lgli/lgrs/nexusstc/upload/zlib · Save

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[Advances in Soft Computing] Soft Methods for Handling Variability and Imprecision Volume 48 || Jean-Marc Bernard (auth.), Didier Dubois, M. Asunción Lubiano, Henri Prade, María Ángeles Gil, Przemysław Grzegorzewski, Olgierd Hryniewicz (eds.) Springer Berlin Heidelberg : Imprint: Springer, 10.1007/97, 2008

Probability theory has been the only well-founded theory of uncertainty for a long time. It was viewed either as a powerful tool for modelling random phenomena, or as a rational approach to the notion of degree of belief. During the last thirty years, in areas centered around decision theory, artificial intelligence and information processing, numerous approaches extending or orthogonal to the existing theory of probability and mathematical statistics have come to the front. The common feature of those attempts is to allow for softer or wider frameworks for taking into account the incompleteness or imprecision of information. Many of these approaches come down to blending interval or fuzzy interval analysis with probabilistic methods. This book gathers contributions to the 4th International Conference on Soft methods in Probability and Statistics. Its aim is to present recent results illustrating such new trends that enlarge the statistical and uncertainty modeling traditions, towards the handling of incomplete or subjective information. It covers a broad scope ranging from philosophical and mathematical underpinnings of new uncertainty theories, with a stress on their impact in the area of statistics and data analysis, to numerical methods and applications to environmental risk analysis and mechanical engineering. A unique feature of this collection is to establish a dialogue between fuzzy random variables and imprecise probability theories.

英语 [en] · PDF · 7.1MB · 2008 · 📘 非小说类图书 · 🚀/lgli/scihub/upload/zlib · Save

nexusstc/Soft Computing in Electromagnetics: Methods and Applications/4137f5318db78545510be28f78441178.pdf

Soft computing in electromagnetics : methods and applications Balamati Choudhury; Rakesh Mohan Jha Cambridge University Press (Virtual Publishing), 2016

Soft computing techniques are emerging as an important tool in solving design, performance and optimisation problems in electromagnetics. Soft Computing in Electromagnetics offers detailed discussion on the application of soft computing concepts in the field of metamaterial antennas, radar absorbers, transmission line characterisation and optimised radar absorbing material (RAM) and introduces implementation of soft computing tools in a relatively new area of metamaterials. The soft computing methods are used to optimise fault detection, electromagnetic propagation and path loss detection. The development of two CAD packages for design of metamaterial split ring resonators (SRR) and path-loss prediction is discussed. The concepts are explained with the help of algorithms and the corresponding software codes. Numerical examples and MATLAB codes are provided throughout the text to facilitate understanding.

英语 [en] · PDF · 8.9MB · 2016 · 📘 非小说类图书 · duxiu/nexusstc · Save

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Modellierung komplexer Prozesse durch naturanaloge Verfahren komplexe adaptive Systeme ; Modellbildungen und -theorie ; neuronale Netze ; Soft-Computing und verwandte Techniken ; mit 11 Tabellen Jï¿1⁄2rn Schmidt Vieweg+Teubner Verlag / GWV Fachverlage, Wiesbaden, Studium, Wiesbaden, 2008

Cover......Page 1 Modellierung komplexer Prozesse durch naturanaloge Verfahren (2009)......Page 3 ISBN 978-3-8348-0400-6......Page 4 Vorwort......Page 5 Inhaltsverzeichnis......Page 7 Einleitung......Page 9 1.1 Soft Computing, Bottom-up und Top-down......Page 13 1.2 Dynamiken komplexer Systeme......Page 18 1.3 Erweiterungen und Anwendungsmöglichkeiten eines universalen Modellschemas......Page 26 1.4 Methodologische Schlussbemerkungen......Page 30 2. Zellularautomaten und Boolesche Netze......Page 33 2.1 Zellularautomaten......Page 34 2.2 Boolesche Netze......Page 43 2.3 Regeln, Topologie und Dynamik – die Ordnungsparameter......Page 48 2.4 Analyse konkreter Modelle......Page 54 3.1 Allgemeine Charakterisierungen......Page 72 3.2 Genetische Algorithmen (GA)......Page 74 3.3 Evolutionsstrategien (ES)......Page 82 3.4 Simulated Annealing......Page 85 3.5 Analyse konkreter Modelle......Page 90 4.1 Biologische Vorbilder......Page 108 4.2 Grundbegriffe......Page 110 4.3 Unterschiedliche Modelle – eine allgemeine Übersicht......Page 126 4.4 Zusammenfassung und „Neurogenerator“......Page 132 4.5 Analyse konkreter Modelle......Page 134 5. Fuzzy-Mengenlehre und Fuzzy-Logik......Page 158 5.1 Einführung in die Grundbegriffe: Von der Unschärfe der Realität......Page 159 5.2 Ein Begriffsexkurs: Wahrscheinlichkeit und Unschärfe......Page 169 5.3 Variationen der Operatoren und unscharfe Logik......Page 172 5.4 Unscharfe Relationen......Page 174 5.5 Experten- und Produktionssysteme sowie Defuzzyfizierungen......Page 177 5.6 Darstellung und Analyse konkreter Modelle......Page 182 6. Hybridisierungen der Basismodelle......Page 191 6.1 Hybride Systeme und Metaparameter......Page 192 6.2 Darstellung von Beispielen......Page 195 6.3 Die Modellierung kognitiver Ontogenese: Ein horizontal gekoppeltes hybrides System......Page 207 7. Resümee und Perspektiven......Page 217 Literaturverzeichnis......Page 219 Sachwortverzeichnis......Page 224

德语 [de] · PDF · 7.7MB · 2008 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save

nexusstc/Soft Computing and Its Applications, Volume One: A Unified Engineering Concept/8f39aeb3bcd637f6e0a6ac10a4b1db45.pdf

Soft Computing and Its Applications, Volume One: A Unified Engineering Concept Kumar S. Ray, PhD Apple Academic Press, Inc. ; CRC Press, 1st edition, Waretown, NJ, Boca Raton, FL, 2014

This is volume 1 of the two-volume set **Soft Computing and Its Applications**. This volume explains the primary tools of soft computing as well as provides an abundance of working examples and detailed design studies. The book starts with coverage of fuzzy sets and fuzzy logic and their various approaches to fuzzy reasoning. Precisely speaking, this book provides a platform for handling different kinds of uncertainties of real-life problems. It introduces the reader to the topic of rough sets. This book’s companion volume, __Volume 2: Fuzzy Reasoning and Fuzzy Control__, will move forward from here to discuss several advanced features of soft computing and application methodologies. This new book: • Discusses the present state of art of soft computing •Includes the existing application areas of soft computing • Presents original research contributions • Discusses the future scope of work in soft computing The book is unique in that it bridges the gap between theory and practice, and it presents several experimental results on synthetic data and real-life data. The book provides a unified platform for applied scientists and engineers in different fields and industries for the application of soft computing tools in many diverse domains of engineering.

英语 [en] · PDF · 30.5MB · 2014 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save

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Unconventional Models of Computation: Third International Conference, UMC 2002, Kobe, Japan, October 15-19, 2002, Proceedings (Lecture Notes in Computer Science, 2509) Manuel Lameiras Campagnolo (auth.) Springer-Verlag Berlin Heidelberg, Lecture Notes in Computer Science, Lecture Notes in Computer Science 2509, 1, 2002

This book constitutes the refereed proceedings of the Third International Conference on Unconventional Models of Computation, UMC 2002, held in Kobe, Japan in October 2002. The 18 revised full papers presented together with eight invited full papers were carefully reviewed and selected from 36 submissions. All major areas of unconventinal computing models are covered, especially quantum computing, DNA computing, membrane computing, cellular computing, and possibilities to break Turing's barrier. The authors address theoretical aspects, practical implementations, as well as philosophical reflections.

英语 [en] · PDF · 5.3MB · 2002 · 📘 非小说类图书 · 🚀/duxiu/lgli/lgrs/nexusstc/scihub/zlib · Save

lgli/A:\compressed\10.1007%2F978-3-322-86843-5.pdf

Betriebswirtschaftliche Anwendungen des Soft Computing: Neuronale Netze, Fuzzy-Systeme und Evolutionäre Algorithmen Prof. Dr. Andreas Zell (auth.), Jörg Biethahn, Albrecht Hönerloh, Jochen Kuhl, Marie-Claire Leisewitz, Volker Nissen, Martin Tietze (eds.) Vieweg+Teubner Verlag, Computational Intelligence, 1, 1998

Prof. Dr. Jörg Biethahn ist Inhaber des Lehrstuhls für Wirtschaftsinformatik I am Institut für Wirtschaftsinformatik der Georg-August-Universität Göttingen. Dort sind auch Dr. Volker Nissen als Wiss. Assistent und Frau Marie-Claire Leisewitz sowie Herr Martin Tietze als Mitarbeiter beschäftigt. Dr. Albrecht Hönerloh arbeitet im Projektmanagement bei Kraft-Jacobs-Suchard, Bremen. Dr. Jochen Kuhl ist als selbständiger Unternehmensberater tätig. Alle Herausgeber verfügen über mehrjährige Erfahrungen im Bereich Soft Computing. Dr. Kuhl und Dr. Nissen sind die Sprecher des Arbeitskreises "Soft Computing in der Betriebswirtschaft" der AG Fuzzy Logik und Soft Computing Norddeutschland (AFN).

德语 [de] · PDF · 10.3MB · 1998 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save

ia/softcomputingfor0000unse_l2h5.pdf

Soft Computing For Intelligent Robotic Systems (studies In Fuzziness And Soft Computing) Lakhmi C. Jain, Toshio Fukuda (eds.) Physica-Springer; Physica, Springer Nature, Heidelberg, 2013

Research results using some of the most advanced soft computing techniques in intelligent robotic systems are presented. The main purpose of this book is to show how the power of soft computing techniques can be exploited in intelligent robotic systems. The main emphasis is on control system for a mobile robot, behavior arbitration for a mobile robot, reinforcement learning of a robot, manipulation of a robot, collision avoidance and automatic design of robots. This book will be useful for application engineers, scientists and researchers who wish to use some of the most advanced soft computing techniques in robotics.

英语 [en] · PDF · 12.4MB · 2013 · 📗 未知类型的图书 · 🚀/ia · Save

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Proceedings / 15. Workshop Computational Intelligence: Dortmund, 16. - 18. November 2005 (german Edition) Ralf Mikut, Markus Reischl Karlsruher Institut für Technologie (KIT). Scientific Publishing c/o KIT-Bibliothek, 2009

Dieser Tagungsband enthält die Beiträge des 15. Workshops Computational Intelligence des Fachausschusses 5.14 der VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik (GMA) und der Fachgruppe Fuzzy-Systeme und Soft-Computing der Gesellschaft für Informatik (GI). Die Schwerpunkte sind Methoden, Anwendungen und Tools für Fuzzy-Systeme, Künstliche Neuronale Netze, Evolutionäre Algorithmen und Data-Mining-Verfahren sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen.

德语 [de] · PDF · 12.3MB · 2009 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save

lgli/Cs_Computer science/CsLn_Lecture notes/A/Artificial Intelligence and Soft Computing - ICAISC 2004, 7 conf.(LNCS3070, Springer, 2004)(ISBN 3540221239)(T)(C)(O)(1237s).djvu

Artificial Intelligence and Soft Computing ― ICAISC 2004: 7th International Conference Zakopane, Poland, June 7–11, 2004 Proceedings (Lecture Notes in Computer Science (3070)) Danilo Ardagna, Chiara Francalanci, Vincenzo Piuri, Fabio Scotti (auth.), Leszek Rutkowski, Jörg H. Siekmann, Ryszard Tadeusiewicz, Lotfi A. Zadeh (eds.) Springer-Verlag Berlin Heidelberg, Lecture Notes in Computer Science, Lecture Notes in Computer Science 3070 Lecture Notes in Artificial Intelligence, 1, 2004

This book constitutes the refereed proceedings of the 7th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2004, held in Zakopane, Poland in June 2004. The 172 revised contributed papers presented together with 17 invited papers were carefully reviewed and selected from 250 submissions. The papers are organized in topical sections on neural networks, fuzzy systems, evolutionary algorithms, rough sets, soft computing in classification, image processing, robotics, multiagent systems, problems in AI, intelligent control, modeling and system identification, medical applications, mechanical applications, and applications in various fields.

英语 [en] · DJVU · 12.6MB · 2004 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save

ia/isbn_9780849398070.pdf

Knowledge-Based Intelligent Techniques in Character Recognition edited by Lakhmi C. Jain, Beatrice Lazzerini Boca Raton, Fla.: CRC Press, CRC Press (Unlimited), [N.p.], 1999

Knowledge-Based Intelligent Techniques in Character Recognition presents research results on intelligent character recognition techniques, reflecting the tremendous worldwide interest in the applications of knowledge-based techniques in this challenging field. This resource will interest anyone involved in computer science, computer engineering, applied mathematics, or related fields. It will also be of use to researchers, application engineers and students who wish to develop successful character recognition systems such as those used in reading addresses in a postal routing system or processing bank checks.Features <h3>Booknews</h3> For electrical engineers working in industry and researchers working in computational research laboratories, outlines the current techniques and cost-effective solutions for applying intelligent techniques to industrial problems, especially designing and monitoring complex and less predictable electrical or mechanical systems. Concentrates on practical solutions rather than theories, and tends more toward illustration than mathematics. The fields discusses include power distribution, transportation, medicine, and communications. Annotation c. by Book News, Inc., Portland, Or.

英语 [en] · PDF · 15.1MB · 1999 · 📗 未知类型的图书 · 🚀/ia · Save

ia/softcomputingina0000kost.pdf

Soft Computing in Acoustics: Applications of Neural Networks, Fuzzy Logic and Rough Sets to Musical Acoustics (Studies in Fuzziness and Soft Computing, 31) Boz̊ena Kostek Physica-Verlag Heidelberg, Springer Nature, Heidelberg, 2013

Applications of some selected soft computing methods to acoustics and sound engineering are presented in this book. The aim of this research study is the implementation of soft computing methods to musical signal analysis and to the recognition of musical sounds and phrases. Accordingly, some methods based on such learning algorithms as neural networks, rough sets and fuzzy-logic were conceived, implemented and tested. Additionally, the above-mentioned methods were applied to the analysis and verification of subjective testing results. The last problem discussed within the framework of this book was the problem of fuzzy control of the classical pipe organ instrument. The obtained results show that computational intelligence and soft computing may be used for solving some vital problems in both musical and architectural acoustics.

英语 [en] · PDF · 13.5MB · 2013 · 📗 未知类型的图书 · 🚀/duxiu/ia · Save

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Soft Computing in Image Processing: Recent Advances (Studies in Fuzziness and Soft Computing, 210) Mike Nachtegael, Dietrich Van der Weken, Etienne E. Kerre, Wilfried Philips Springer London, Limited, Studies in Fuzziness and Soft Computing, Studies in Fuzziness and Soft Computing, 1, 2007

Images have always been very important in human life. Their applications range from primitive communication between humans of all ages to advanced technologies in the industrial, medical and military field. The increased possibilities to capture and analyze images have contributed to the largeness that the scientific field of "image processing" has become today. Many techniques are being applied, including soft computing. "Soft Computing in Image Processing: Recent Advances" follows the edited volumes "Fuzzy Techniques in Image Processing" (volume 52, published in 2000) and "Fuzzy Filters for Image Processing" (volume 122, published in 2003), and covers a wide range of both practical and theoretical applications of soft computing in image processing. The 16 excellent chapters of the book have been grouped into five parts: Applications in Remote Sensing, Applications in Image Retrieval, Applications in Image Analysis, Other Applications, and Theoretical Contributions. The focus of the book is on practical applications, which makes it interesting for every researcher that is involved with soft computing, image processing, or both scientific branches.

英语 [en] · PDF · 18.3MB · 2007 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save

lgli/D:\!genesis\library.nu\e0\_195104.e0dd183a1415d3ead3db3ca51c91f9c6.pdf

A New Paradigm of Knowledge Engineering by Soft Computing (Fuzzy Logic Systems Institute (Flsi) Soft Computing Series, Volume 5) Japan) International Conference on Soft Computing 1998 (Iizuka-Shi World Scientific Publishing Company, Incorporated, World Scientific Publishing Company, Singapore, 2001

Soft Computing (sc) Consists Of Several Computing Paradigms, Including Neural Networks, Fuzzy Set Theory, Approximate Reasoning, And Derivative-free Optimization Methods Such As Genetic Algorithms. The Integration Of Those Constituent Methodologies Forms The Core Of Sc. In Addition, The Synergy Allows Sc To Incorporate Human Knowledge Effectively, Deal With Imprecision And Uncertainty, And Learn To Adapt To Unknown Or Changing Environments For Better Performance. Together With Other Modern Technologies, Sc And Its Applications Exert Unprecedented Influence On Intelligent Systems That Mimic Human Intelligence In Thinking, Learning, Reasoning, And Many Other Aspects. Knowledge Engineering (ke), Which Deals With Knowledge Acquisition, Representation, Validation, Inferencing, Explanation, And Maintenance, Has Made Significant Progress Recently, Owing To The Indefatigable Efforts Of Researchers. Undoubtedly, The Hot Topics Of Data Mining And Knowledge/data Discovery Have Injected New Life Into The Classical Ai World. This Book Tells Readers How Ke Has Been Influenced And Extended By Sc And How Sc Will Be Helpful In Pushing The Frontier Of Ke Further. It Is Intended For Researchers And Graduate Students To Use As A Reference In The Study Of Knowledge Engineering And Intelligent Systems. The Reader Is Expected To Have A Basic Knowledge Of Fuzzy Logic, Neural Networks, Genetic Algorithms, And Knowledge-based Systems. Contents:knowledge Engineering And Soft Computing — An Introduction (l-y Ding)fuzzy Knowledge-based Systems:linguistic Integrity: A Framework For Fuzzy Modeling — Afreli Algorithm (j Espinosa & J Vandewalle)a New Approach To Acquisition Of Comprehensible Fuzzy Rules (h Ohno & T Furuhashi)fuzzy Rule Generation With Fuzzy Singleton-type Reasoning Method (y Shi & M Mizumoto)antecedent Validity Adaptation Principle For Table Look-up Scheme (p-t Chan & A B Rad)fuzzy Spline Interpolation In Sparse Fuzzy Rule Bases (m F Kawaguchi & M Miyakoshi)revision Principle Applied For Approximate Reasoning (l-y Ding Et Al.)handling Null Queries With Compound Fuzzy Attributes (s-l Wang & Y-j Tsai)fuzzy System Description Language (k Otsuka Et Al.)knowledge Representation, Integration, And Discovery By Soft Computing:knowledge Representation And Similarity Measure In Learning A Vague Legal Concept (m Q Xu Et Al.)trend Fuzzy Sets And Recurrent Fuzzy Rules For Ordered Dataset Modelling (j F Baldwin Et Al.)approaches To The Design Of Classification Systems From Numerical Data And Linguistic Knowledge (h Ishibuchi Et Al.)a Clustering Based On Self-organizing Map And Knowledge Discovery By Neural Network (k Nakagawa Et Al.)probabilistic Rough Induction (j-z Dong Et Al.)data Mining Via Linguistic Summaries Of Databases: An Interactive Approach (j Kacprzyk & S Zadrozny)and Other Papers Readership: Graduate Students, Researchers And Lecturers In Knowledge Engineering And Soft Computing. Keywords:fuzzy Logic;neural Networks;evolutionary Computation;soft Computing;knowledge-based Systems;knowledge Representation;knowledge Integration;knowledge Discovery;knowledge Engineering;clustering

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ia/isbn_3540211098.pdf

Applications of Learning Classifier Systems Larry Bull (ed.) Springer Berlin, Springer Nature, Berlin, Heidelberg, 2012

The field called Learning Classifier Systems is populated with romantics. Why shouldn't it be possible for computer programs to adapt, learn, and develop while interacting with their environments? In particular, why not systems that, like organic populations, contain competing, perhaps cooperating, entities evolving together? John Holland was one of the earliest scientists with this vision, at a time when so-called artificial intelligence was in its infancy and mainly concerned with preprogrammed systems that didn't learn. that, like organisms, had sensors, took Instead, Holland envisaged systems actions, and had rich self-generated internal structure and processing. In so doing he foresaw and his work prefigured such present day domains as reinforcement learning and embedded agents that are now displacing the older "standard Af' . One focus was what Holland called "classifier systems": sets of competing rule like "classifiers", each a hypothesis as to how best to react to some aspect of the environment--or to another rule. The system embracing such a rule "popu lation" would explore its available actions and responses, rewarding and rating the active rules accordingly. Then "good" classifiers would be selected and re produced, mutated and even crossed, a la Darwin and genetics, steadily and reliably increasing the system's ability to cope. Erscheinungsdatum: 16.04.2004

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lgli/I:\usenet_ger\Soft.Computing.in.der.Bioinformatik.-.Springer.-.2006.-.tlw27n.pdf

Soft Computing in der Bioinformatik: Eine grundlegende Einführung und Übersicht (eXamen.press) Jürgen Paetz Springer Berlin, EXamen.press, 1. Aufl, Berlin, 2006

Der Begriff "Soft Computing" bezeichnet ein zunehmend an Bedeutung gewinnendes Thema. Dahinter verbergen sich Methoden wie Neuronale Netze, Fuzzy-Logik, Maschinelles Lernen, evolutionäre Algorithmen und naturanaloge Algorithmen. Das Gemeinsame dieser Verfahren ist ihr Potenzial im Umgang mit komplexen und vage formulierten Datenmengen. Alle wichtigen Themen des Soft Computing werden behandelt und mit ihren zahlreichen Anwendungen in der Bioinformatik verknüpft, wie beispielsweise Sequenzanalyse, Strukturvorhersage, Genexpressionsanalyse, Systembiologie und Moleküldesign. Insgesamt erhält der Leser anhand einer formal ausgearbeiteten Darstellung einen fundierten Überblick über das Gesamtgebiet. Im Anhang wird zudem eine nützliche Einführung in das Programmpaket "Matlab" gegeben. Das Buch eignet sich für alle an Soft Computing und Bioinformatik interessierten Leser, die bereits mit den Grundlagen der Mathematik und Informatik vertraut sind.

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ia/isbn_9783540024910.pdf

Applied Decision Support with Soft Computing (Studies in Fuzziness and Soft Computing (124)) Xing Huo Yu; Janusz Kacprzyk Springer Berlin, Springer Nature, Berlin, Heidelberg, 2012

soft Computing Has Provided Sophisticated Methodologies For The Development Of Intelligent Decision Support Systems. Fast Advances In Soft Computing Technologies, Such As Fuzzy Logic And Systems, Artificial Neural Networks And Evolutionary Computation, Have Made Available Powerful Problem Representation And Modelling Paradigms, And Learning And Optimisation Mechanisms For Addressing Modern Decision Making Issues. This Book Provides A Comprehensive Coverage Of Up-to-date Conceptual Frameworks In Broadly Perceived Decision Support Systems And Successful Applications. Different From Other Existing Books, This Volume Predominately Focuses On Applied Decision Support With Soft Computing. Areas Covered Include Planning, Management Finance And Administration In Both The Private And Public Sectors.

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lgli/Дэвидсон-Пайлон - Вероятностное программирование на Python. Байесовский вывод и алгоритмы - 2019.pdf

Вероятностное программирование на Python. Байесовский вывод и алгоритмы: 16+ Кэмерон Дэвидсон-Пайлон; [перевод с английского И. Пальти, К. Русецкий] Питер, Библиотека программиста, 2019

Байесовские методы пугают формулами многих «айтишников», но без анализа статистики и вероятностей сейчас не обойтись. Кэмерон Дэвидсон-Пайлон рассказывает о байесовском методе с точки зрения программиста-практика, работающего с многофункциональным языком PyMC и библиотеками NumPy, SciPy и Matplotlib. Раскрывая роль байесовских выводов при А/В-тестировании, выявлении мошенничества и в других насущных задачах, вы не только легко разберетесь в этой нетривиальной теме, но и начнете применять полученные знания для достижения своих целей. https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

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Soft computing applications in sensor networks Misra, Sudip; Pal, Sankar K Chapman and Hall/CRC, CRC Press (Unlimited), Boca Raton, 2017

This book uses tutorials and new material to describe the basic concepts of soft-computing which potentially can be used in real-life sensor network applications. It is organized in a manner that exemplifies the use of an assortment of soft-computing applications for solving different problems in sensor networking. Written by worldwide experts, the chapters provide a balanced mixture of different problems concerning channel access, routing, coverage, localization, lifetime maximization and target tracking using emerging soft-computing applications.

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lgli/Cs_Computer science/CsLn_Lecture notes/A/Agent-Based Hybrid Intelligent Systems.. An Agent-Based Framework for Complex Problem Solving(LNCS2938, Springer, 2004)(ISBN 3540209085)(196s)_CsLn_.pdf

Lecture Notes in Artificial Intelligence 2938 Agent-Based Hybrid Intelligent Systems An Agent-Based Framework for Complex Problem Solving Zili Zhang, Chengqi Zhang (auth.) Springer-Verlag Berlin Heidelberg, Lecture Notes in Computer Science, Lecture Notes in Computer Science 2938 : Lecture Notes in Artificial Intelligence, 1, 2004

Solving complex problems in real-world contexts, such as financial investment planning or mining large data collections, involves many different sub-tasks, each of which requires different techniques. To deal with such problems, a great diversity of intelligent techniques are available, including traditional techniques like expert systems approaches and soft computing techniques like fuzzy logic, neural networks, or genetic algorithms. These techniques are complementary approaches to intelligent information processing rather than competing ones, and thus better results in problem solving are achieved when these techniques are combined in hybrid intelligent systems. Multi-Agent Systems are ideally suited to model the manifold interactions among the many different components of hybrid intelligent systems. This book introduces agent-based hybrid intelligent systems and presents a framework and methodology allowing for the development of such systems for real-world applications. The authors focus on applications in financial investment planning and data mining.

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ia/designofanalogfu0000dual.pdf

Design of analog fuzzy logic controllers in CMOS technologies : implementation, test, and application by Carlos Dualibe, Michel Verleysen, Paul G.A. Jespers Springer US, Springer Nature, Boston, 2003

Nowadays, real-time applications of Fuzzy Logic in different domains are being increasingly reported. ASIC-based analog hardware becomes an interesting solution for these kinds of applications because it benefits from: savings on silicon surface and power consumption, readily accomplishment with strict timing constraints and cost-effective production. This book focuses in-depth on the VLSI CMOS implementation and application of programmable analog Fuzzy Logic Controllers following a mixed-signal philosophy. This is to say, signals are processed in the analog domain whereas programmability is achieved by means of standard digital memories. This approach highlights the following crucial aspects: •The comprehensive study and analysis of the main analog fuzzy operators: Fuzzy Membership Functions, T-Norm, T-CoNorm and Defuzzifier circuits. •The study and development of mixed-signal Fuzzy Controllers architectures targeting the requirements for different applications. •The fabrication and test of full-ended demonstrators. •The partial fabrication and test of a prototype corresponding to a real-time Fuzzy Logic application in the field of Signal Processing.

英语 [en] · PDF · 12.2MB · 2003 · 📗 未知类型的图书 · 🚀/ia · Save

upload/misc/ThoseBooks/No Category/No Category/Bayesian Methods for Hackers Probabilistic Programming and Bayesian Methods (9780133902839, 2015)/9780133902839(1).azw3

Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics Series) Davidson-Pilon, Cameron Davidson-Pilon Pearson Education, Addison Wesley Data & Analytics Series, Boston, 2015

Master Bayesian Inference through Practical Examples and ComputationWithout Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practicefreeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. Youll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once youve mastered these techniques, youll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes Learning the Bayesian state of mind and its practical implications Understanding how computers perform Bayesian inference Using the PyMC Python library to program Bayesian analyses Building and debugging models with PyMC Testing your models goodness of fit Opening the black box of the Markov Chain Monte Carlo algorithm to see how and why it works Leveraging the power of the Law of Large Numbers Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning Using loss functions to measure an estimates weaknesses based on your goals and desired outcomes Selecting appropriate priors and understanding how their influence changes with dataset size Overcoming the exploration versus exploitation deciding when pretty good is good enough Using Bayesian inference to improve A/B testing Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

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nexusstc/Knowledge-free & Learning-based Methods in Intelligent Game Playing/aef381b9933ff5d5b6aa47bcb5464185.pdf

Knowledge-Free and Learning-Based Methods in Intelligent Game Playing Jacek Mańdziuk Springer-Verlag Berlin Heidelberg, Springer Nature, Berlin, Heidelberg, 2010

Humans and machines are very di?erent in their approaches to game pl- ing. Humans use intuition, perception mechanisms, selective search, creat- ity, abstraction, heuristic abilities and other cognitive skills to compensate their (comparably) slow information processing speed, relatively low m- ory capacity, and limited search abilities. Machines, on the other hand, are extremely fast and infallible in calculations, capable of e?ective brute-for- type search, use “unlimited” memory resources, but at the same time are poor at using reasoning-based approaches and abstraction-based methods. The above major discrepancies in the human and machine problem solving methods underlined the development of traditional machine game playing as being focused mainly on engineering advances rather than cognitive or psychological developments. In other words, as described by Winkler and F ̈ urnkranz [347, 348] with respect to chess, human and machine axes of game playing development are perpendicular, but the most interesting, most promising, and probably also most di?cult research area lies on the junction between human-compatible knowledge and machine compatible processing.I undoubtedly share this point of view and strongly believe that the future of machine game playing lies in implementation of human-type abilities (- straction,intuition,creativity,selectiveattention,andother)whilestilltaking advantage of intrinsic machine skills. Thebookisfocusedonthedevelopmentsandprospectivechallengingpr- lems in the area of mind gameplaying (i.e. playinggames that require mental skills) using Computational Intelligence (CI) methods, mainly neural n- works, genetic/evolutionary programming and reinforcement learning.

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scihub/10.1007/978-3-319-05515-2.pdf

[Advances in Intelligent Systems and Computing] Soft Computing in Artificial Intelligence Volume 270 || Young Im Cho, Eric T. Matson (eds.) Springer International Publishing : Imprint : Springer, 10.1007/97, 2014

This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, individual role adaptation for team sports, application of polynomial neural networks, recursive neuro-fuzzy algorithm for water management, application of interactive genetic algorithm, and Artificial Neural Network (ANN) model. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verification.

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ia/softcomputingfor0000venu.pdf

Soft Computing for Data Mining Applications (Studies in Computational Intelligence, 190) K. R. Venugopal; K.G. Srinivasa; L. M. Patnaik Berlin: Springer Verlag, Springer Nature, Berlin, Heidelberg, 2009

The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems,?nance,marketing,healthcare,telecommunications,andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However,the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions. Erscheinungsdatum: 11.03.2009

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lgli/Cs_Computer science/CsLn_Lecture notes/R/Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, 11 conf., RSFDGrC 2007(LNCS4482, Springer, 2007)(ISBN 9783540725299)(599s).pdf

Rough Sets, Fuzzy Sets, Data Mining and Granular Computing : 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings. Aijun An, Jerzy Stefanowski, Sheela Ramanna, Cory J. Butz, Wit Andrzej Jankowski, Andrzej Skowron (auth.), Aijun An, Jerzy Stefanowski, Sheela Ramanna, Cory J. Butz, Witold Pedrycz, Guoyin Wang (eds.) Springer-Verlag Berlin Heidelberg, Lecture Notes in Computer Science, Lecture Notes in Computer Science 4482, 1, 2007

This volume contains the papers selected for presentation at the 11th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2007), a part of the Joint Rough Set Symposium (JRS 2007) organized by Infobright Inc. and York University. JRS 2007 was held for the ?rst time during May 14–16, 2007 in MaRS Discovery District, Toronto, Canada. It consisted of two conferences: RSFDGrC 2007 and the Second Int- national Conference on Rough Sets and Knowledge Technology (RSKT 2007). The two conferences that constituted JRS 2007 investigated rough sets as an emerging methodology established more than 25 years ago by Zdzis law Pawlak. Roughsettheoryhasbecomeanintegralpartofdiversehybridresearchstreams. In keeping with this trend, JRS 2007 encompassed rough and fuzzy sets, kno- edgetechnologyanddiscovery,softandgranularcomputing,dataprocessingand mining, while maintaining an emphasis on foundations and applications. RSFDGrC 2007 followed in the footsteps of well-established international initiatives devoted to the dissemination of rough sets research, held so far in Canada, China, Japan, Poland, Sweden, and the USA. RSFDGrC was ?rst - ganized as the 7th International Workshop on Rough Sets, Data Mining and Granular Computing held in Yamaguchi, Japan in 1999. Its key feature was to stress the role of integrating intelligent information methods to solve real-world, large, complex problems concerned with uncertainty and fuzziness. RSFDGrC achieved the status of a bi-annual international conference, starting from 2003 in Chongqing, China.

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upload/newsarch_ebooks_2025_10/2020/04/27/Soft Computing Applications for Renewable Energy and Energy .pdf

Soft Computing Applications for Renewable Energy and Energy Efficiency Maria del Socorro García Cascales; Juan Miguel Sánchez Lozano; Antonio David Masegosa Arredondo; Carlos Cruz Corona IGI Global, Advances in Environmental Engineering and Green Technologies, Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pa., 17033, USA), 2015

As the climate and environment continue to fluctuate, researchers are urgently looking for new ways to preserve our limited resources and prevent further environmental degradation. The answer can be found through computer science, a field that is evolving at precisely the time it is needed most. Soft Computing Applications for Renewable Energy and Energy Efficiency brings together the latest technological research in computational intelligence and fuzzy logic as a way to care for our environment. This reference work highlights current advances and future trends in environmental sustainability using the principles of soft computing, making it an essential resource for students, researchers, engineers, and practitioners in the fields of project engineering and energy science.

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nexusstc/Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference/51d73c88197e1de5d8128f839a61d0e2.pdf

Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference (Addison-Wesley Data & Analytics) (Addison-Wesley Data & Analytics) Davidson-Pilon, Cameron Davidson-Pilon Addison-Wesley Professional, Addison-Wesley Data and Analytics Series, 1st, 2015

Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.

英语 [en] · PDF · 17.9MB · 2015 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save

lgli/A:\compressed\10.1007%2F978-3-7908-1881-9.pdf

Fuzzy and Neural: Interactions and Applications (Studies in Fuzziness and Soft Computing, 25) Prof. James J. Buckley, Dr. Thomas Feuring (auth.) Physica-Verlag Heidelberg, Studies in Fuzziness and Soft Computing, Studies in Fuzziness and Soft Computing 25, 1, 1998

This book is about recent research area described as the intersection of fuzzy sets, (layered, feedforward) neural nets and evolutionary algorithms. Also called "soft computing". The treatment is elementary in that all "proofs" have been relegated to the references and the only mathematical prerequisite is elementary differential calculus. No previous knowledge of neural nets nor fuzzy sets is needed. Most of the discussion centers around the authors' own research in this area over the last ten years. The book brings together results on: (1) approximations between neural nets and fuzzy systems; (2) building hybrid neural nets for fuzzy systems; (3) approximations between fuzzy neural nets for fuzzy systems. New results include the use of evolutionary algorithms to train fuzzy neural nets and the introduction of a "fuzzy teaching machine". The interaction between fuzzy and neural is also illustrated in the use of neural nets to solve fuzzy problems and the use of fuzzy neural nets to solve the "overfitting" problem of regular neural nets. Besides giving a comprehensive theoretical survey of these results the authors also survey the unsolved problems in this exciting, new, area of research.

英语 [en] · PDF · 8.6MB · 1998 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save

lgli/66.pdf

Soft Computing as Transdisciplinary Science and Technology: Proceedings of the fourth IEEE International Workshop WSTST ́05 (Advances in Intelligent and Soft Computing, 29) Ajith Abraham (editor), Yasuhiko Dote (editor), Takeshi Furuhashi (editor), Mario Köppen (editor), Azuma Ohuchi (editor), Yukio Ohsawa (editor) Springer-Verlag Berlin Heidelberg, Advances in soft computing, 29, Berlin, Heidelberg, 2005

This book presents the proceedings of the Fourth International Workshop on Soft Computing as Transdisciplinary Science and Technology (WSTST '05), May 25-27, 2005, Muroran, Japan. It brings together the original work of international soft computing/computational intelligence researchers, developers, practitioners, and users. This proceedings provide contributions to all areas of soft computing including intelligent hybrid systems, agent-based systems, intelligent data mining, decision support systems, cognitive and reactive distributed artificial intelligence (AI), internet modelling, human interface, and applications in science and technology.

英语 [en] · PDF · 38.8MB · 2005 · 📘 非小说类图书 · 🚀/lgli/lgrs · Save

duxiu/initial_release/40323657.zip

Soft Computing Approach to Pattern Recognition and Image Processing (Series in Machine Perception and Artificial Intelligence) Ashish Ghosh, Sankar K Pal, Sankar K. Pal World Scientific Publishing Company, Series in machine perception and artificial intelligence, v. 53, River Edge, NJ, 2003

A collection of 16 articles containing reviews and material. They describe the development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets, with real life applications. One of the most exciting advances in pattern recognition over the last decade is represented by multiple classifier fusion.

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lgli/A:\compressed\10.1007%2F978-3-540-37057-4.pdf

Interpretability Issues in Fuzzy Modeling Jorge Casillas, Oscar Cordón, Francisco Herrera, Luis Magdalena (auth.), Dr. Jorge Casillas, Dr. Oscar Cordón, Dr. Francisco Herrera, Dr. Luis Magdalena (eds.) Springer-Verlag Berlin Heidelberg, Studies in Fuzziness and Soft Computing, Studies in Fuzziness and Soft Computing 128, 1, 2003

Fuzzy modeling has become one of the most productive and successful results of fuzzy logic. Among others, it has been applied to knowledge discovery, automatic classification, long-term prediction, or medical and engineering analysis. The research developed in the topic during the last two decades has been mainly focused on exploiting the fuzzy model flexibility to obtain the highest accuracy. This approach usually sets aside the interpretability of the obtained models. However, we should remember the initial philosophy of fuzzy sets theory directed to serve the bridge between the human understanding and the machine processing. In this challenge, the ability of fuzzy models to express the behavior of the real system in a comprehensible manner acquires a great importance. This book collects the works of a group of experts in the field that advocate the interpretability improvements as a mechanism to obtain well balanced fuzzy models.

英语 [en] · PDF · 28.6MB · 2003 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save

lgli/D:\!genesis\library.nu\aa\_21979.aaf09b16d3cdcbd376d8f8a32e62782d.pdf

Proceedings / 17. Workshop Computational Intelligence: Dortmund, 5. -7. Dezember 2007 (german Edition) Ralf Mikut, Markus Reischl, Dortmund Workshop Computational Intelligence Technische Informationsbibliothek u. Universitätsbibliothek Univ.-Verl. Karlsruhe, 2007, 2009

Dieser Tagungsband enthält die Beiträge des 17. Workshops "Computational Intelligence" des Fachausschusses 5.14 der VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik (GMA) und der Fachgruppe "Fuzzy-Systeme und Soft-Computing" der Gesellschaft für Informatik (GI). Die Schwerpunkte sind Fuzzy-Systeme, Künstliche Neuronale Netze, Evolutionäre Algorithmen und Data-Mining-Verfahren sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen.

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lgli/D:\HDD4\!genesis\SPR_NEW_2013-12\bok%3A978-1-4615-4673-3.pdf

Design Considerations of Time in Fuzzy Systems Jernej Virant (auth.) Springer US : Imprint : Springer, Applied Optimization, Applied Optimization 35, 1, 2000

Fuzzy theory is an interesting name for a method that has been highly effective in a wide variety of significant, real-world applications. A few examples make this readily apparent. As the result of a faulty design the method of computer-programmed trading, the biggest stock market crash in history was triggered by a small fraction of a percent change in the interest rate in a Western European country. A fuzzy theory ap proach would have weighed a number of relevant variables and the ranges of values for each of these variables. Another example, which is rather simple but pervasive, is that of an electronic thermostat that turns on heat or air conditioning at a specific temperature setting. In fact, actual comfort level involves other variables such as humidity and the location of the sun with respect to windows in a home, among others. Because of its great applied significance, fuzzy theory has generated widespread activity internationally. In fact, institutions devoted to research in this area have come into being. As the above examples suggest, Fuzzy Systems Theory is of fundamen tal importance for the analysis and design of a wide variety of dynamic systems. This clearly manifests the fundamental importance of time con siderations in the Fuzzy Systems design approach in dynamic systems. This textbook by Prof. Dr. Jernej Virant provides what is evidently a uniquely significant and comprehensive treatment of this subject on the international scene.

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ia/computationalint0000rutk.pdf

Computational Intelligence : Methods and Techniques Leszek Rutkowski Springer Spektrum. in Springer-Verlag GmbH, Springer Nature (Textbooks & Major Reference Works), Berlin, Heidelberg, 2008

Publication of this book is a special event. This valuable title ?lls a se- ous gap in domestic science and technical literature. At the same time it introduces a reader to the most recent achievements in the quickly dev- oping branch of knowledge which the computational intelligence has been for several years. The ?eld, which is a subject of this book, is one of those important ?elds of science which enable to process information included in data and give their reasonable interpretation programmed by a user. Recent decades have brought a stormy development of computer te- niquesandrelatedcomputationalmethods.Togetherwiththeirappearance and quick progress, theoretical and applied sciences developed as well, - ablingtheusertofullyutilizenewlycreatedcomputationalpotentialandto getknowledgeoutofincreasingwealthofdata.Thedevelopmentofcom- tational intelligence is then strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Without them the development of this ?eld would be almost impossible, and its application practically marginal. That is why these techniques have especially developed in recent years. The development of computational intelligence systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. Nature when undertakes intelligent actions processes data in p- allel regulating and adjusting these actions through feedback mechanisms. Erscheinungsdatum: 29.05.2008

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nexusstc/Towards an Advanced Modelling of Complex Economic Phenomena/3607c0243422dd4e4233109f93d16733.pdf

Towards an Advanced Modelling of Complex Economic Phenomena : Pretopological and Topological Uncertainty Research Tools Jaime Gil Aluja, Ana Maria Gil Lafuente (auth.) Springer-Verlag Berlin Heidelberg, Studies in Fuzziness and Soft Computing, Studies in Fuzziness and Soft Computing 276, 1, 2012

Little by little we are being provided with an arsenal of operative instruments of a non-numerical nature, in the shape of models and algorithms, capable of providing answers to the ́ aggressions ́ which our economics and management systems must withstand, coming from an environment full of turmoil. ℗ In the work which we are presenting, we dare to propose a set of elements from which we hope arise focuses capable of renewing those structures of economic thought which are upheld by the geometrical idea. ℗ The concepts of pretopology and topology, habitually marginalized in economics and management studies, have centred our interest in recent times.℗ We consider that it is not possible to conceive formal structures capable of representing the Darwinism concept of economic behaviour today without recurring to this fundamental generalisation of metric spaces. ℗ In our attempts to find a solid base to the structures proposed for the treatment of economic phenomena, we have frequently resorted to the theory of clans and the theory of affinities with results which we believe to be satisfactory.℗ We would like to go further, establishing, if possible, the connection between their axiomatics at the same time as developing some uncertain pretopologies and topologies capable of linking previously unconnected theories, at the same time easing the creation of other new theories

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duxiu/initial_release/40755264.zip

Soft Computing for Control of Non-Linear Dynamical Systems (Studies in Fuzziness and Soft Computing, 63) Oscar Castillo and patricia melin, Castillo, Oscar, Melin, Patricia, Oscar Castillo, Patricia Melin Physica-Verlag HD : Imprint : Physica, 2001, 2001

\"The book describes the application of soft computing techniques to modelling, simulation and control of non-linear dynamical systems. Hybrid intelligence systems, which integrate different techniques and mathematical models, are also presented. The book covers the basics of fuzzy logic, neural networks, evolutionary computation, chaos and fractal theory. It also presents in detail different hybrid architectures for developing intelligent control systems for applications in robotics, reactors, manufacturing, aircraft systems and economics.\"--Jacket The book describes the application of soft computing techniques to modelling, simulation and control of non-linear dynamical systems. Hybrid intelligence systems, which integrate different techniques and mathematical models, are also presented. The book covers the basics of fuzzy logic, neural networks, evolutionary computation, chaos and fractal theory. It also describes in detail different hybrid architectures for developing intelligent control systems for applications in robotics, reactors, manufacturing, aircraft systems and economics. This book presents a unified view of modelling, simulation, and control of non linear dynamical systems using soft computing techniques and fractal theory. This book presents a unified view of modelling, simulation, and control of non linear dynamical systems using soft computing techniques and fractal theory. We describe in this book, new methods for modelling, simulation, and control of dynamical systems using soft computing techniques and fractal theory.

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Introduction to soft computing : neuro-fuzzy and genetic algorithms Chakraborty, Udit; Roy, Samir Pearson Education India, Always learning, Always learning, New Delhi, India, 2013

Soft Computing Is A Branch Of Computer Science That Deals With A Family Of Methods That Imitate Human Intelligence. This Is Done With The Goal Of Creating Tools That Will Contain Some Human-like Capabilities (such As Learning, Reasoning And Decision-making). This Book Covers The Entire Gamut Of Soft Computing, Including Fuzzy Logic, Rough Sets, Artificial Neural Networks, And Various Evolutionary Algorithms. It Offers A Learner-centric Approach Where Each New Concept Is Introduced With Carefully Designed Examples/instances To Train The Learner.

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nexusstc/Decoherence and Entropy in Complex Systems: Selected Lectures from DICE 2002/7ffa5942a170efecde50c66f0a1f55de.djvu

Decoherence and Entropy in Complex Systems: Selected Lectures from DICE 2002 (Lecture Notes in Physics (633)) Hans-Thomas Elze; International Workshop on Decoherence, Information, Complexity and Entropy Springer Berlin Heidelberg : Imprint: Springer, Lecture Notes in Physics, Lecture notes in physics 633; Physics and astronomy online library, 1, 2004

The contributions to this volume are based on selected lectures from the first international workshop on decoherence, information, complexity and entropy (DICE). These contributions reflect and acknowledge the growing importance of common concepts behind seemingly different fields such as quantum mechanics, general relativity and statistical physics in a form accessible to nonspecialist researchers. Many of the presentations include original results, which are published here for the first time.

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lgli/1603.pdf

Soft-Ware 2002: Computing in an Imperfect World: First International Conference, Soft-Ware 2002 Belfast, Northern Ireland, April 8-10, 2002 Proceedings (Lecture Notes in Computer Science, 2311) David Bustard (editor), Weiru Liu (editor) Springer Berlin, Lecture notes in computer science -- 2311., Berlin, New York, Germany, 2002

This was the ?rst conference of a new series devoted to the e?ective handling of soft issues in the design, development, and operation of computing systems. The conference brought together contributors from a range of relevant disciplines, including arti?cial intelligence, information systems, software engineering, and systems engineering. The keynote speakers, Piero Bonissone, Ray Paul, Sir Tony Hoare, Michael Jackson, and Derek McAuley have interests and experience that collectively span all of these ?elds. Soft issues involve information or knowledge that is uncertain, incomplete, or contradictory. Examples of where such issues arise include: – requirements management and software quality control in software engine- ing, – con?ict or multiple sources information management in information systems, – decision making/prediction in business management systems, – quality control in networks and user services in telecommunications, – traditional human rationality modeling in arti?cial intelligence, – data analysis in machine learning and data mining, – control management in engineering. The concept of dealing with uncertainty became prominent in the arti?cial intel- gence community nearly 20 years ago, when researchers realized that addressing uncertainty was an essential part of representing and reasoning about human knowledge in intelligent systems. The main methodologies that have emerged in this area are soft computing and computational intelligence. Erscheinungsdatum: 27.03.2002

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Proceedings of the International Conference on Soft Computing Systems: ICSCS 2015, Volume 2 (Advances in Intelligent Systems and Computing Book 398) L Padma Suresh, Bijaya Ketan Panigrahi (eds.) Springer (India) Private Limited, Advances in Intelligent Systems and Computing, Advances in Intelligent Systems and Computing 398, 2, 1, 2016

The book is a collection of high-quality peer-reviewed research papers presented in International Conference on Soft Computing Systems (ICSCS 2015) held at Noorul Islam Centre for Higher Education, Chennai, India. These research papers provide the latest developments in the emerging areas of Soft Computing in Engineering and Technology. The book is organized in two volumes and discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. It presents invited papers from the inventors/originators of new applications and advanced technologies.

英语 [en] · PDF · 21.4MB · 2016 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/upload/zlib · Save