Genetic Algorithms And Fuzzy Logic Systems
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Genetic Algorithms And Fuzzy Logic Systems
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Author : Elie Sanchez
language : en
Publisher: World Scientific
Release Date : 1997
Genetic Algorithms And Fuzzy Logic Systems written by Elie Sanchez and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
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.
Genetic Fuzzy Systems Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases
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Author : Oscar Cordon
language : en
Publisher: World Scientific
Release Date : 2001-07-13
Genetic Fuzzy Systems Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases written by Oscar Cordon and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-13 with Computers categories.
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.
Genetic Algorithms And Fuzzy Multiobjective Optimization
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Author : Masatoshi Sakawa
language : en
Publisher: Springer Science & Business Media
Release Date : 2002
Genetic Algorithms And Fuzzy Multiobjective Optimization written by Masatoshi Sakawa and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Business & Economics categories.
Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a wide range of actual real world applications. The theoretical material and applications place special stress on interactive decision-making aspects of fuzzy multiobjective optimization for human-centered systems in most realistic situations when dealing with fuzziness. The intended readers of this book are senior undergraduate students, graduate students, researchers, and practitioners in the fields of operations research, computer science, industrial engineering, management science, systems engineering, and other engineering disciplines that deal with the subjects of multiobjective programming for discrete or other hard optimization problems under fuzziness. Real world research applications are used throughout the book to illustrate the presentation. These applications are drawn from complex problems. Examples include flexible scheduling in a machine center, operation planning of district heating and cooling plants, and coal purchase planning in an actual electric power plant.
Neural Networks Fuzzy Logic And Genetic Algorithm
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Author : S. RAJASEKARAN
language : en
Publisher: PHI Learning Pvt. Ltd.
Release Date : 2003-01-01
Neural Networks Fuzzy Logic And Genetic Algorithm written by S. RAJASEKARAN and has been published by PHI Learning Pvt. Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-01-01 with Computers categories.
This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the technologies is demonstrated on architectures such as Fuzzy-Back-propagation Networks (NN-FL), Simplified Fuzzy ARTMAP (NN-FL), and Fuzzy Associative Memories. The book also gives an exhaustive discussion of FL-GA hybridization. Every architecture has been discussed in detail through illustrative examples and applications. The algorithms have been presented in pseudo-code with a step-by-step illustration of the same in problems. The applications, demonstrative of the potential of the architectures, have been chosen from diverse disciplines of science and engineering. This book with a wealth of information that is clearly presented and illustrated by many examples and applications is designed for use as a text for courses in soft computing at both the senior undergraduate and first-year post-graduate engineering levels. It should also be of interest to researchers and technologists desirous of applying soft computing technologies to their respective fields of work.
Genetic Fuzzy Systems
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Author : Oscar Cord¢n
language : en
Publisher: World Scientific
Release Date : 2001
Genetic Fuzzy Systems written by Oscar Cord¢n and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
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.
Fusion Of Neural Networks Fuzzy Systems And Genetic Algorithms
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Author : Lakhmi C. Jain
language : en
Publisher: CRC Press
Release Date : 2020-01-29
Fusion Of Neural Networks Fuzzy Systems And Genetic Algorithms written by Lakhmi C. Jain and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-29 with Computers categories.
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 Logic And Soft Computing
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Author : Bernadette Bouchon-Meunier
language : en
Publisher: World Scientific
Release Date : 1995
Fuzzy Logic And Soft Computing written by Bernadette Bouchon-Meunier and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
Soft computing is a new, emerging discipline rooted in a group of technologies that aim to exploit the tolerance for imprecision and uncertainty in achieving solutions to complex problems. The principal components of soft computing are fuzzy logic, neurocomputing, genetic algorithms and probabilistic reasoning.This volume is a collection of up-to-date articles giving a snapshot of the current state of the field. It covers the whole expanse, from theoretical foundations to applications. The contributors are among the world leaders in the field.
Fuzzy Modeling And Genetic Algorithms For Data Mining And Exploration
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Author : Earl Cox
language : en
Publisher: Academic Press
Release Date : 2005-02
Fuzzy Modeling And Genetic Algorithms For Data Mining And Exploration written by Earl Cox and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02 with Computers categories.
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.
Introduction To Neural Networks Fuzzy Logic Genetic Algorithms
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Author : Sudarshan K. Valluru
language : en
Publisher:
Release Date : 2010
Introduction To Neural Networks Fuzzy Logic Genetic Algorithms written by Sudarshan K. Valluru and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Fuzzy logic categories.
A New Paradigm Of Knowledge Engineering By Soft Computing
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Author : Liya Ding
language : en
Publisher: World Scientific
Release Date : 2001
A New Paradigm Of Knowledge Engineering By Soft Computing written by Liya Ding and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.
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.