Compensatory Genetic Fuzzy Neural Networks And Their Applications
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Compensatory Genetic Fuzzy Neural Networks And Their Applications
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Author : Yan-Qing Zhang
language : en
Publisher: World Scientific
Release Date : 1998
Compensatory Genetic Fuzzy Neural Networks And Their Applications written by Yan-Qing Zhang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.
This book presents a powerful hybrid intelligent system based on fuzzy logic, neural networks, genetic algorithms and related intelligent techniques. The new compensatory genetic fuzzy neural networks have been widely used in fuzzy control, nonlinear system modeling, compression of a fuzzy rule base, expansion of a sparse fuzzy rule base, fuzzy knowledge discovery, time series prediction, fuzzy games and pattern recognition. This effective soft computing system is able to perform both linguistic-word-level fuzzy reasoning and numerical-data-level information processing. The book also proposes various novel soft computing techniques.
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.
Type 2 Fuzzy Neural Networks And Their Applications
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Author : Rafik Aziz Aliev
language : en
Publisher: Springer
Release Date : 2014-09-08
Type 2 Fuzzy Neural Networks And Their Applications written by Rafik Aziz Aliev and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-08 with Computers categories.
This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination with other paradigms of Soft Computing technology such as Neuro-Computing and Evolutionary Computing. It provides a self-contained exposition of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making, system identification and other real problems. Type-2 Fuzzy Neural Networks and Their Applications is helpful for teachers and students of universities and colleges, for scientists and practitioners from various fields such as control, decision analysis, pattern recognition and similar fields.
Foundations Of Generic Optimization
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Author : R. Lowen
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-27
Foundations Of Generic Optimization written by R. Lowen 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 2007-10-27 with Mathematics categories.
This is a comprehensive overview of the basics of fuzzy control, which also brings together some recent research results in soft computing, in particular fuzzy logic using genetic algorithms and neural networks. This book offers researchers not only a solid background but also a snapshot of the current state of the art in this field.
Fuzzy Neural Intelligent Systems
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Author : Hongxing Li
language : en
Publisher: CRC Press
Release Date : 2018-10-03
Fuzzy Neural Intelligent Systems written by Hongxing Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Computers categories.
Although fuzzy systems and neural networks are central to the field of soft computing, most research work has focused on the development of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems, especially their mathematical foundations. Fuzzy Neural Intelligent Systems fills this gap. It develops a mathematical basis for fuzzy neural networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing their focus into three main areas of interest, the authors give a systematic, comprehensive treatment of the relevant concepts and modern practical applications: Fundamental concepts and theories for fuzzy systems and neural networks. Foundation for fuzzy neural networks and important related topics Case examples for neuro-fuzzy systems, fuzzy systems, neural network systems, and fuzzy-neural systems Suitable for self-study, as a reference, and ideal as a textbook, Fuzzy Neural Intelligent Systems is accessible to students with a basic background in linear algebra and engineering mathematics. Mastering the material in this textbook will prepare students to better understand, design, and implement fuzzy neural systems, develop new applications, and further advance the field.
Fuzzy Neural Network Theory And Application
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Author : Puyin Liu
language : en
Publisher: World Scientific
Release Date : 2004-06-07
Fuzzy Neural Network Theory And Application written by Puyin Liu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-07 with Computers categories.
This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering.
Applications And Science Of Neural Networks Fuzzy Systems And Evolutionary Computation
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Author :
language : en
Publisher:
Release Date : 2002
Applications And Science Of Neural Networks Fuzzy Systems And Evolutionary Computation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Evolutionary computation categories.
Modular Neural Networks And Type 2 Fuzzy Systems For Pattern Recognition
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Author : Patricia Melin
language : en
Publisher: Springer
Release Date : 2011-10-25
Modular Neural Networks And Type 2 Fuzzy Systems For Pattern Recognition written by Patricia Melin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-25 with Technology & Engineering categories.
This book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.
Advances In Fuzzy Logic Neural Networks And Genetic Algorithms
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Author : Takeshi Furuhashi
language : en
Publisher: Springer
Release Date : 1995-11-15
Advances In Fuzzy Logic Neural Networks And Genetic Algorithms written by Takeshi Furuhashi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-11-15 with Computers categories.
This book presents 14 rigorously reviewed revised papers selected from more than 50 submissions for the 1994 IEEE/ Nagoya-University World Wisepersons Workshop, WWW'94, held in August 1994 in Nagoya, Japan. The combination of approaches based on fuzzy logic, neural networks and genetic algorithms are expected to open a new paradigm of machine learning for the realization of human-like information processing systems. The first six papers in this volume are devoted to the combination of fuzzy logic and neural networks; four papers are on how to combine fuzzy logic and genetic algorithms. Four papers investigate challenging applications of fuzzy systems and of fuzzy-genetic algorithms.
Fuzzy Neural Networks For Real Time Control Applications
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Author : Erdal Kayacan
language : en
Publisher: Butterworth-Heinemann
Release Date : 2015-10-07
Fuzzy Neural Networks For Real Time Control Applications written by Erdal Kayacan and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-07 with Mathematics categories.
AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book! Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book. A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis. You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are: • Gradient descent • Levenberg-Marquardt • Extended Kalman filter In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced. The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or doctorate university studies. We hope that this book will serve its main purpose successfully. Parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis Contains algorithms that are applicable to real time systems Introduces fast and simple adaptation rules for type-1 and type-2 fuzzy neural networks Number of case studies both in identification and control Provides MATLAB® codes for some algorithms in the book