Genetic Fuzzy Systems

Genetic Fuzzy Systems

Author: Oscar Cord¢n

Publisher: World Scientific

Published: 2001

Total Pages: 492

ISBN-13: 9789810240172

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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.


Fuzzy Systems

Fuzzy Systems

Author: Hung T. Nguyen

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 532

ISBN-13: 1461555051

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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.


Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Author: Nikola K. Kasabov

Publisher: Marcel Alencar

Published: 1996

Total Pages: 581

ISBN-13: 0262112124

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Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.


Fuzzy Algorithms

Fuzzy Algorithms

Author: Zheru Chi

Publisher: World Scientific

Published: 1996

Total Pages: 242

ISBN-13: 9789810226978

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http://www.worldscientific.com/worldscibooks/10.1142/3132


Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Author: Lakhmi C. Jain

Publisher: CRC Press

Published: 2020-01-29

Total Pages: 363

ISBN-13: 1000715124

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Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise in solving problems, but a definitive theoretical basis does not yet exist for their design. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms integrates neural net, fuzzy system, and evolutionary computing in system design that enables its readers to handle complexity - offsetting the demerits of one paradigm by the merits of another. This book presents specific projects where fusion techniques have been applied. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques in modern engineering systems. These specific applications include: direct frequency converters electro-hydraulic systems motor control toaster control speech recognition vehicle routing fault diagnosis Asynchronous Transfer Mode (ATM) communications networks telephones for hard-of-hearing people control of gas turbine aero-engines telecommunications systems design Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms covers the spectrum of applications - comprehensively demonstrating the advantages of fusion techniques in industrial applications.


Fuzzy Systems Engineering

Fuzzy Systems Engineering

Author: Witold Pedrycz

Publisher: John Wiley & Sons

Published: 2007-10-12

Total Pages: 550

ISBN-13: 0470168951

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A self-contained treatment of fuzzy systems engineering, offering conceptual fundamentals, design methodologies, development guidelines, and carefully selected illustrative material Forty years have passed since the birth of fuzzy sets, in which time a wealth of theoretical developments, conceptual pursuits, algorithmic environments, and other applications have emerged. Now, this reader-friendly book presents an up-to-date approach to fuzzy systems engineering, covering concepts, design methodologies, and algorithms coupled with interpretation, analysis, and underlying engineering knowledge. The result is a holistic view of fuzzy sets as a fundamental component of computational intelligence and human-centric systems. Throughout the book, the authors emphasize the direct applicability and limitations of the concepts being discussed, and historical and bibliographical notes are included in each chapter to help readers view the developments of fuzzy sets from a broader perspective. A radical departure from current books on the subject, Fuzzy Systems Engineering presents fuzzy sets as an enabling technology whose impact, contributions, and methodology stretch far beyond any specific discipline, making it applicable to researchers and practitioners in engineering, computer science, business, medicine, bioinformatics, and computational biology. Additionally, three appendices and classroom-ready electronic resources make it an ideal textbook for advanced undergraduate- and graduate-level courses in engineering and science.


Fuzzy Decision Making In Modeling And Control

Fuzzy Decision Making In Modeling And Control

Author: Joao M Costa Sousa

Publisher: World Scientific

Published: 2002-12-03

Total Pages: 356

ISBN-13: 9814489263

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Decision making and control are two fields with distinct methods for solving problems, and yet they are closely related. This book bridges the gap between decision making and control in the field of fuzzy decisions and fuzzy control, and discusses various ways in which fuzzy decision making methods can be applied to systems modeling and control.Fuzzy decision making is a powerful paradigm for dealing with human expert knowledge when one is designing fuzzy model-based controllers. The combination of fuzzy decision making and fuzzy control in this book can lead to novel control schemes that improve the existing controllers in various ways. The following applications of fuzzy decision making methods for designing control systems are considered:• Fuzzy decision making for enhancing fuzzy modeling. The values of important parameters in fuzzy modeling algorithms are selected by using fuzzy decision making.• Fuzzy decision making for designing signal-based fuzzy controllers. The controller mappings and the defuzzification steps can be obtained by decision making methods.• Fuzzy design and performance specifications in model-based control. Fuzzy constraints and fuzzy goals are used.• Design of model-based controllers combined with fuzzy decision modules. Human operator experience is incorporated for the performance specification in model-based control.The advantages of bringing together fuzzy control and fuzzy decision making are shown with multiple examples from real and simulated control systems.


Genetic Algorithms And Fuzzy Logic Systems Soft Computing Perspectives

Genetic Algorithms And Fuzzy Logic Systems Soft Computing Perspectives

Author: Elie Sanchez

Publisher: World Scientific

Published: 1997-03-15

Total Pages: 252

ISBN-13: 9814499803

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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.


Fuzzy Logic

Fuzzy Logic

Author: Vladimir Dimitrov

Publisher: Physica

Published: 2013-12-06

Total Pages: 397

ISBN-13: 3790818062

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At the beginning of the new millennium, fuzzy logic opens a new challenging perspective in information processing. This perspective emerges out of the ideas of the founder of fuzzy logic - Lotfi Zadeh, to develop 'soft' tools for direct computing with human perceptions. The enigmatic nature of human perceptions manifests in their unique capacity to generalize, extract patterns and capture both the essence and the integrity of the events and phenomena in human life. This capacity goes together with an intrinsic imprecision of the perception-based information. According to Zadeh, it is because of the imprecision of the human imprecision that they do not lend themselves to meaning representation through the use of precise methods based on predicate logic. This is the principal reason why existing scientific theories do not have the capability to operate on perception-based information. We are at the eve of the emergence of a theory with such a capability. Its applicative effectiveness has been already demonstrated through the industrial implementation of the soft computing - a powerful intelligent technology centred in fuzzy logic. At the focus of the papers included in this book is the knowledge and experience of the researchers in relation both to the engineering applications of soft computing and to its social and philosophical implications at the dawn of the third millennium. The papers clearly demonstrate that Fuzzy Logic revolutionizes general approaches for solving applied problems and reveals deep connections between them and their solutions.