Genetic Fuzzy Systems Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases
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Author |
: Oscar Cordon |
Publisher |
: World Scientific |
Total Pages |
: 489 |
Release |
: 2001-07-13 |
ISBN-10 |
: 9789814494458 |
ISBN-13 |
: 9814494453 |
Rating |
: 4/5 (58 Downloads) |
Synopsis Genetic Fuzzy Systems: Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases by : Oscar Cordon
In recent years, a great number of publications have explored the use of genetic algorithms as a tool for designing fuzzy systems. Genetic Fuzzy Systems explores and discusses this symbiosis of evolutionary computation and fuzzy logic. The book summarizes and analyzes the novel field of genetic fuzzy systems, paying special attention to genetic algorithms that adapt and learn the knowledge base of a fuzzy-rule-based system. It introduces the general concepts, foundations and design principles of genetic fuzzy systems and covers the topic of genetic tuning of fuzzy systems. It also introduces the three fundamental approaches to genetic learning processes in fuzzy systems: the Michigan, Pittsburgh and Iterative-learning methods. Finally, it explores hybrid genetic fuzzy systems such as genetic fuzzy clustering or genetic neuro-fuzzy systems and describes a number of applications from different areas.Genetic Fuzzy System represents a comprehensive treatise on the design of the fuzzy-rule-based systems using genetic algorithms, both from a theoretical and a practical perspective. It is a valuable compendium for scientists and engineers concerned with research and applications in the domain of fuzzy systems and genetic algorithms.
Author |
: Elie Sanchez |
Publisher |
: World Scientific |
Total Pages |
: 254 |
Release |
: 1997 |
ISBN-10 |
: 9810224230 |
ISBN-13 |
: 9789810224233 |
Rating |
: 4/5 (30 Downloads) |
Synopsis Genetic Algorithms and Fuzzy Logic Systems by : Elie Sanchez
Ever since fuzzy logic was introduced by Lotfi Zadeh in the mid-sixties and genetic algorithms by John Holland in the early seventies, these two fields widely been subjects of academic research the world over. During the last few years, they have been experiencing extremely rapid growth in the industrial world, where they have been shown to be very effective in solving real-world problems. These two substantial fields, together with neurocomputing techniques, are recognized as major parts of soft computing: a set of computing technologies already riding the waves of the next century to produce the human-centered intelligent systems of tomorrow; the collection of papers presented in this book shows the way. The book also contains an extensive bibliography on fuzzy logic and genetic algorithms.
Author |
: Yaochu Jin |
Publisher |
: Physica |
Total Pages |
: 276 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9783790817713 |
ISBN-13 |
: 3790817716 |
Rating |
: 4/5 (13 Downloads) |
Synopsis Advanced Fuzzy Systems Design and Applications by : Yaochu Jin
Fuzzy rule systems have found a wide range of applications in many fields of science and technology. Traditionally, fuzzy rules are generated from human expert knowledge or human heuristics for relatively simple systems. In the last few years, data-driven fuzzy rule generation has been very active. Compared to heuristic fuzzy rules, fuzzy rules generated from data are able to extract more profound knowledge for more complex systems. This book presents a number of approaches to the generation of fuzzy rules from data, ranging from the direct fuzzy inference based to neural net works and evolutionary algorithms based fuzzy rule generation. Besides the approximation accuracy, special attention has been paid to the interpretabil ity of the extracted fuzzy rules. In other words, the fuzzy rules generated from data are supposed to be as comprehensible to human beings as those generated from human heuristics. To this end, many aspects of interpretabil ity of fuzzy systems have been discussed, which must be taken into account in the data-driven fuzzy rule generation. In this way, fuzzy rules generated from data are intelligible to human users and therefore, knowledge about unknown systems can be extracted.
Author |
: Earl Cox |
Publisher |
: Academic Press |
Total Pages |
: 554 |
Release |
: 2005-02 |
ISBN-10 |
: 9780121942755 |
ISBN-13 |
: 0121942759 |
Rating |
: 4/5 (55 Downloads) |
Synopsis Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration by : Earl Cox
Foundations and ideas -- Principal model types -- Approaches to model building -- Fundamental concepts of fuzzy logic -- Fundamental concepts of fuzzy systems -- Fuzzy SQL and intelligent queries -- Fuzzy clustering -- Fuzzy rule induction -- Fundamental concepts of genetic algorithms -- Genetic resource scheduling optimization -- Genetic tuning of fuzzy models.
Author |
: Hung T. Nguyen |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 532 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9781461555056 |
ISBN-13 |
: 1461555051 |
Rating |
: 4/5 (56 Downloads) |
Synopsis Fuzzy Systems by : Hung T. Nguyen
The analysis and control of complex systems have been the main motivation for the emergence of fuzzy set theory since its inception. It is also a major research field where many applications, especially industrial ones, have made fuzzy logic famous. This unique handbook is devoted to an extensive, organized, and up-to-date presentation of fuzzy systems engineering methods. The book includes detailed material and extensive bibliographies, written by leading experts in the field, on topics such as: Use of fuzzy logic in various control systems. Fuzzy rule-based modeling and its universal approximation properties. Learning and tuning techniques for fuzzy models, using neural networks and genetic algorithms. Fuzzy control methods, including issues such as stability analysis and design techniques, as well as the relationship with traditional linear control. Fuzzy sets relation to the study of chaotic systems, and the fuzzy extension of set-valued approaches to systems modeling through the use of differential inclusions. Fuzzy Systems: Modeling and Control is part of The Handbooks of Fuzzy Sets Series. The series provides a complete picture of contemporary fuzzy set theory and its applications. This volume is a key reference for systems engineers and scientists seeking a guide to the vast amount of literature in fuzzy logic modeling and control.
Author |
: Michael Anthony Lee |
Publisher |
: |
Total Pages |
: 410 |
Release |
: 1994 |
ISBN-10 |
: UCAL:X54368 |
ISBN-13 |
: |
Rating |
: 4/5 (68 Downloads) |
Synopsis Automatic Design and Adaptation of Fuzzy Systems and Genetic Algorithms Using Soft Computing Techniques by : Michael Anthony Lee
Author |
: Witold Pedrycz |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 399 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9781461313656 |
ISBN-13 |
: 1461313651 |
Rating |
: 4/5 (56 Downloads) |
Synopsis Fuzzy Modelling by : Witold Pedrycz
Fuzzy Modelling: Paradigms and Practice provides an up-to-date and authoritative compendium of fuzzy models, identification algorithms and applications. Chapters in this book have been written by the leading scholars and researchers in their respective subject areas. Several of these chapters include both theoretical material and applications. The editor of this volume has organized and edited the chapters into a coherent and uniform framework. The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models. Fuzzy Modelling: Paradigms and Practice provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.
Author |
: Natarajan Meghanathan |
Publisher |
: Springer |
Total Pages |
: 511 |
Release |
: 2010-12-25 |
ISBN-10 |
: 9783642178818 |
ISBN-13 |
: 3642178812 |
Rating |
: 4/5 (18 Downloads) |
Synopsis Advanced Computing by : Natarajan Meghanathan
This volume constitutes the third of three parts of the refereed proceedings of the First International Conference on Computer Science and Information Technology, CCSIT 2010, held in Bangalore, India, in January 2011. The 46 revised full papers presented in this volume were carefully reviewed and selected. The papers are organized in topical sections on soft computing, such as AI, Neural Networks, Fuzzy Systems, etc.; distributed and parallel systems and algorithms; security and information assurance; ad hoc and ubiquitous computing; wireless ad hoc networks and sensor networks.
Author |
: Jorge Casillas |
Publisher |
: Springer |
Total Pages |
: 392 |
Release |
: 2013-11-11 |
ISBN-10 |
: 9783540370581 |
ISBN-13 |
: 3540370587 |
Rating |
: 4/5 (81 Downloads) |
Synopsis Accuracy Improvements in Linguistic Fuzzy Modeling by : Jorge Casillas
Fuzzy modeling usually comes with two contradictory requirements: interpretability, which is the capability to express the real system behavior in a comprehensible way, and accuracy, which is the capability to faithfully represent the real system. In this framework, one of the most important areas is linguistic fuzzy modeling, where the legibility of the obtained model is the main objective. This task is usually developed by means of linguistic (Mamdani) fuzzy rule-based systems. An active research area is oriented towards the use of new techniques and structures to extend the classical, rigid linguistic fuzzy modeling with the main aim of increasing its precision degree. Traditionally, this accuracy improvement has been carried out without considering the corresponding interpretability loss. Currently, new trends have been proposed trying to preserve the linguistic fuzzy model description power during the optimization process. Written by leading experts in the field, this volume collects some representative researcher that pursue this approach.
Author |
: Tomasa Calvo Sánchez |
Publisher |
: Springer |
Total Pages |
: 252 |
Release |
: 2016-05-10 |
ISBN-10 |
: 9783319304212 |
ISBN-13 |
: 3319304216 |
Rating |
: 4/5 (12 Downloads) |
Synopsis Fuzzy Logic and Information Fusion by : Tomasa Calvo Sánchez
This book offers a timely report on key theories and applications of soft-computing. Written in honour of Professor Gaspar Mayor on his 70th birthday, it primarily focuses on areas related to his research, including fuzzy binary operators, aggregation functions, multi-distances, and fuzzy consensus/decision models. It also discusses a number of interesting applications such as the implementation of fuzzy mathematical morphology based on Mayor-Torrens t-norms. Importantly, the different chapters, authored by leading experts, present novel results and offer new perspectives on different aspects of Mayor’s research. The book also includes an overview of evolutionary fuzzy systems, a topic that is not one of Mayor’s main areas of interest, and a final chapter written by the Spanish pioneer in fuzzy logic, Professor E. Trillas. Computer and decision scientists, knowledge engineers and mathematicians alike will find here an authoritative overview of key soft-computing concepts and techniques.