Fuzzy Evolutionary Computation

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Fuzzy Evolutionary Computation

Author : Witold Pedrycz
Publisher : Springer Science & Business Media
ISBN 13 : 1461561353
Total Pages : 325 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Fuzzy Evolutionary Computation by : Witold Pedrycz

Download or read book Fuzzy Evolutionary Computation written by Witold Pedrycz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: As of today, Evolutionary Computing and Fuzzy Set Computing are two mature, wen -developed, and higbly advanced technologies of information processing. Bach of them has its own clearly defined research agenda, specific goals to be achieved, and a wen setUed algorithmic environment. Concisely speaking, Evolutionary Computing (EC) is aimed at a coherent population -oriented methodology of structural and parametric optimization of a diversity of systems. In addition to this broad spectrum of such optimization applications, this paradigm otTers an important ability to cope with realistic goals and design objectives reflected in the form of relevant fitness functions. The GA search (which is often regarded as a dominant domain among other techniques of EC such as evolutionary strategies, genetic programming or evolutionary programming) delivers a great deal of efficiency helping navigate through large search spaces. The main thrust of fuzzy sets is in representing and managing nonnumeric (linguistic) information. The key notion (whose conceptual as weH as algorithmic importance has started to increase in the recent years) is that of information granularity. It somewhat concurs with the principle of incompatibility coined by L. A. Zadeh. Fuzzy sets form a vehic1e helpful in expressing a granular character of information to be captured. Once quantified via fuzzy sets or fuzzy relations, the domain knowledge could be used efficiently very often reducing a heavy computation burden when analyzing and optimizing complex systems.

Fundamentals of Computational Intelligence

Author : James M. Keller
Publisher : John Wiley & Sons
ISBN 13 : 111921436X
Total Pages : 378 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Fundamentals of Computational Intelligence by : James M. Keller

Download or read book Fundamentals of Computational Intelligence written by James M. Keller and published by John Wiley & Sons. This book was released on 2016-07-13 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

NEURAL NETWORKS, FUZZY SYSTEMS AND EVOLUTIONARY ALGORITHMS : SYNTHESIS AND APPLICATIONS

Author : S. RAJASEKARAN
Publisher : PHI Learning Pvt. Ltd.
ISBN 13 : 812035334X
Total Pages : 576 pages
Book Rating : 4.1/5 (23 download)

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Book Synopsis NEURAL NETWORKS, FUZZY SYSTEMS AND EVOLUTIONARY ALGORITHMS : SYNTHESIS AND APPLICATIONS by : S. RAJASEKARAN

Download or read book NEURAL NETWORKS, FUZZY SYSTEMS AND EVOLUTIONARY ALGORITHMS : SYNTHESIS AND APPLICATIONS written by S. RAJASEKARAN and published by PHI Learning Pvt. Ltd.. This book was released on 2017-05-01 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this book provides a comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence, which in recent years, has turned synonymous to it. The constituent technologies discussed comprise neural network (NN), fuzzy system (FS), evolutionary algorithm (EA), and a number of hybrid systems, which include classes such as neuro-fuzzy, evolutionary-fuzzy, and neuro-evolutionary systems. The hybridization of the technologies is demonstrated on architectures such as fuzzy backpropagation network (NN-FS hybrid), genetic algorithm-based backpropagation network (NN-EA hybrid), simplified fuzzy ARTMAP (NN-FS hybrid), fuzzy associative memory (NN-FS hybrid), fuzzy logic controlled genetic algorithm (EA-FS hybrid) and evolutionary extreme learning machine (NN-EA hybrid) 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 the courses in soft computing at both the senior undergraduate and first-year postgraduate levels of computer science and engineering. It should also be of interest to researchers and technologists desirous of applying soft computing technologies to their respective fields of work.

Soft Computing

Author : Andrea Tettamanzi
Publisher : Springer Science & Business Media
ISBN 13 : 3662043351
Total Pages : 335 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Soft Computing by : Andrea Tettamanzi

Download or read book Soft Computing written by Andrea Tettamanzi and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

Genetic Fuzzy Systems

Author :
Publisher :
ISBN 13 : 9814494453
Total Pages : pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Genetic Fuzzy Systems by :

Download or read book Genetic Fuzzy Systems written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Intelligence

Author : Nazmul Siddique
Publisher : John Wiley & Sons
ISBN 13 : 1118534816
Total Pages : 524 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Computational Intelligence by : Nazmul Siddique

Download or read book Computational Intelligence written by Nazmul Siddique and published by John Wiley & Sons. This book was released on 2013-05-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB® exercises and applications in each chapter Presents the synergies of technologies of computational intelligence such as evolutionary fuzzy neural fuzzy and evolutionary neural systems Considers real world problems in the domain of systems modelling, control and optimization Contains a foreword written by Lotfi Zadeh Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing is an ideal text for final year undergraduate, postgraduate and research students in electrical, control, computer, industrial and manufacturing engineering.

Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Author : Lakhmi C. Jain
Publisher : CRC Press
ISBN 13 : 1000715124
Total Pages : 363 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms by : Lakhmi C. Jain

Download or read book Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms written by Lakhmi C. Jain and published by CRC Press. This book was released on 2020-01-29 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Genetic Fuzzy Systems

Author : Oscar Cord¢n
Publisher : World Scientific
ISBN 13 : 9789810240172
Total Pages : 492 pages
Book Rating : 4.2/5 (41 download)

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Book Synopsis Genetic Fuzzy Systems by : Oscar Cord¢n

Download or read book Genetic Fuzzy Systems written by Oscar Cord¢n and published by World Scientific. This book was released on 2001 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Fundamentals of Computational Intelligence

Author : James M. Keller
Publisher : John Wiley & Sons
ISBN 13 : 1119214343
Total Pages : 378 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Fundamentals of Computational Intelligence by : James M. Keller

Download or read book Fundamentals of Computational Intelligence written by James M. Keller and published by John Wiley & Sons. This book was released on 2016-07-12 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II

Author : Bruno Bosacchi
Publisher : SPIE-International Society for Optical Engineering
ISBN 13 :
Total Pages : 326 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II by : Bruno Bosacchi

Download or read book Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation II written by Bruno Bosacchi and published by SPIE-International Society for Optical Engineering. This book was released on 1999 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation

Author :
Publisher :
ISBN 13 :
Total Pages : 304 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation by :

Download or read book Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation written by and published by . This book was released on 2002 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Intelligence and Its Applications

Author : H K Lam
Publisher : World Scientific
ISBN 13 : 1908977078
Total Pages : 320 pages
Book Rating : 4.9/5 (89 download)

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Book Synopsis Computational Intelligence and Its Applications by : H K Lam

Download or read book Computational Intelligence and Its Applications written by H K Lam and published by World Scientific. This book was released on 2012-07-17 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on computational intelligence techniques and their applications — fast-growing and promising research topics that have drawn a great deal of attention from researchers over the years. It brings together many different aspects of the current research on intelligence technologies such as neural networks, support vector machines, fuzzy logic and evolutionary computation, and covers a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications. Fundamental concepts and essential analysis of various computational techniques are presented to offer a systematic and effective tool for better treatment of different applications, and simulation and experimental results are included to illustrate the design procedure and the effectiveness of the approaches. Sample Chapter(s) Chapter 1: Maximal Margin Algorithms for Pose Estimation (658 KB) Contents:Evolutionary Computation and Its Applications:Maximal Margin Algorithms for Pose Estimation (Ying Guo and Jiaming Li)Polynomial Modeling in a Dynamic Environment Based on a Particle Swarm Optimization (Kit Yan Chan and Tharam S Dillon)Restoration of Half-toned Color-quantized Images Using Particle Swarm Optimization with Multi-wavelet Mutation (Frank H F Leung, Benny C W Yeung and Y H Chan)Fuzzy Logics and Their Applications:Hypoglycemia Detection for Insulin-dependent Diabetes Mellitus: Evolved Fuzzy Inference System Approach (S H Ling, P P San and H T Nguyen)Neural Networks and Their Applications:Study of Limit Cycle Behavior of Weights of Perceptron (C Y F Ho and B W K Ling)Artificial Neural Network Modeling with Application to Nonlinear Dynamics (Yi Zhao)Solving Eigen-problems of Matrices by Neural Networks (Yiguang Liu, Zhisheng You, Bingbing Liu and Jiliu Zhou)Automated Screw Insertion Monitoring Using Neural Networks: A Computational Intelligence Approach to Assembly in Manufacturing (Bruno Lara, Lakmal D Seneviratne and Kaspar Althoefer)Support Vector Machines and Their Applications:On the Applications of Heart Disease Risk Classification and Hand-written Character Recognition Using Support Vector Machines (S R Alty, H K Lam and J Prada)Nonlinear Modeling Using Support Vector Machine for Heart Rate Response to Exercise (Weidong Chen, Steven W Su, Yi Zhang, Ying Guo, Nghir Nguyen, Branko G Celler and Hung T Nguyen)Machine Learning-based Nonlinear Model Predictive Control for Heart Rate Response to Exercise (Yi Zhang, Steven W Su, Branko G Celler and Hung T Nguyen)Intelligent Fault Detection and Isolation of HVAC System Based on Online Support Vector Machine (Davood Dehestani, Ying Guo, Sai Ho Ling, Steven W Su and Hung T Nguyen) Readership: Graduates and researchers in computer science, especially those specialising in artificial intelligence, neural networks, fuzzy logic and pattern recognition. Keywords:Evolutionary Computation;Fuzzy Logic;Neural Networks;Support Vector MachineKey Features:Covers wide-ranging applications from pattern recognition, control systems to biomedical applications. Various computational techniques are proposed and presented in detail for the treatment of various problemsMost of the applications in this book are real and high impact, such as hypoglycaemia, detection for diabetes patients, cardio respiratory response estimation, pattern recognition and pose estimationAddresses important related problems and difficulties using the collective experiences and knowledge from the contributors, who are each prominent in their own area of research

Computational Intelligence

Author : Russell C. Eberhart
Publisher : Elsevier
ISBN 13 : 0080553834
Total Pages : 496 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Computational Intelligence by : Russell C. Eberhart

Download or read book Computational Intelligence written by Russell C. Eberhart and published by Elsevier. This book was released on 2011-04-18 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence: Concepts to Implementations provides the most complete and practical coverage of computational intelligence tools and techniques to date. This book integrates various natural and engineering disciplines to establish Computational Intelligence. This is the first comprehensive textbook on the subject, supported with lots of practical examples. It asserts that computational intelligence rests on a foundation of evolutionary computation. This refreshing view has set the book apart from other books on computational intelligence. This book lays emphasis on practical applications and computational tools, which are very useful and important for further development of the computational intelligence field. Focusing on evolutionary computation, neural networks, and fuzzy logic, the authors have constructed an approach to thinking about and working with computational intelligence that has, in their extensive experience, proved highly effective. The book moves clearly and efficiently from concepts and paradigms to algorithms and implementation techniques by focusing, in the early chapters, on the specific con. It explores a number of key themes, including self-organization, complex adaptive systems, and emergent computation. It details the metrics and analytical tools needed to assess the performance of computational intelligence tools. The book concludes with a series of case studies that illustrate a wide range of successful applications. This book will appeal to professional and academic researchers in computational intelligence applications, tool development, and systems. Moves clearly and efficiently from concepts and paradigms to algorithms and implementation techniques by focusing, in the early chapters, on the specific concepts and paradigms that inform the authors' methodologies Explores a number of key themes, including self-organization, complex adaptive systems, and emergent computation Details the metrics and analytical tools needed to assess the performance of computational intelligence tools Concludes with a series of case studies that illustrate a wide range of successful applications Presents code examples in C and C++ Provides, at the end of each chapter, review questions and exercises suitable for graduate students, as well as researchers and practitioners engaged in self-study

Handbook of Fuzzy Computation

Author : E Ruspini
Publisher : CRC Press
ISBN 13 : 1420050397
Total Pages : 1229 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Handbook of Fuzzy Computation by : E Ruspini

Download or read book Handbook of Fuzzy Computation written by E Ruspini and published by CRC Press. This book was released on 2020-03-05 with total page 1229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Initially conceived as a methodology for the representation and manipulation of imprecise and vague information, fuzzy computation has found wide use in problems that fall well beyond its originally intended scope of application. Many scientists and engineers now use the paradigms of fuzzy computation to tackle problems that are either intractable

Evolutionary Computation

Author : D. Dumitrescu
Publisher : CRC Press
ISBN 13 : 9780849305887
Total Pages : 424 pages
Book Rating : 4.3/5 (58 download)

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Book Synopsis Evolutionary Computation by : D. Dumitrescu

Download or read book Evolutionary Computation written by D. Dumitrescu and published by CRC Press. This book was released on 2000-06-22 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid advances in evolutionary computation have opened up a world of applications-a world rapidly growing and evolving. Decision making, neural networks, pattern recognition, complex optimization/search tasks, scheduling, control, automated programming, and cellular automata applications all rely on evolutionary computation. Evolutionary Computation presents the basic principles of evolutionary computing: genetic algorithms, evolution strategies, evolutionary programming, genetic programming, learning classifier systems, population models, and applications. It includes detailed coverage of binary and real encoding, including selection, crossover, and mutation, and discusses the (m+l) and (m,l) evolution strategy principles. The focus then shifts to applications: decision strategy selection, training and design of neural networks, several approaches to pattern recognition, cellular automata, applications of genetic programming, and more.

Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Author : Lakhmi C. Jain
Publisher : CRC Press
ISBN 13 : 1000722945
Total Pages : 366 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms by : Lakhmi C. Jain

Download or read book Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms written by Lakhmi C. Jain and published by CRC Press. This book was released on 2020-01-29 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Modelling

Author : Witold Pedrycz
Publisher : Springer Science & Business Media
ISBN 13 : 1461313651
Total Pages : 399 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Fuzzy Modelling by : Witold Pedrycz

Download or read book Fuzzy Modelling written by Witold Pedrycz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.