Genetic Fuzzy Systems

Genetic Fuzzy Systems PDF Book Detail:
Author: Oscar Cord¢n
Publisher: World Scientific
ISBN: 9789810240172
Size: 42.21 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 462
View: 3683

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Book Description: 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 Logic Systems

Genetic Algorithms and Fuzzy Logic Systems PDF Book Detail:
Author: Elie Sanchez
Publisher: World Scientific
ISBN: 9789810224233
Size: 39.32 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 240
View: 5649

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Book Description: 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.

Compensatory Genetic Fuzzy Neural Networks And Their Applications

Compensatory Genetic Fuzzy Neural Networks and Their Applications PDF Book Detail:
Author: Yan-Qing Zhang
Publisher: World Scientific
ISBN: 9789810233495
Size: 71.80 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 186
View: 2219

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Book Description: 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.

Structural Health Monitoring Using Genetic Fuzzy Systems

Structural Health Monitoring Using Genetic Fuzzy Systems PDF Book Detail:
Author: Prashant M. Pawar
Publisher: Springer Science & Business Media
ISBN: 9780857299079
Size: 75.15 MB
Format: PDF, ePub, Docs
Category : Science
Languages : en
Pages : 132
View: 432

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Book Description: Structural health monitoring (SHM) has emerged as a prominent research area in recent years owing to increasing concerns about structural safety, and the need to monitor and extend the lives of existing structures. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. The use of a genetic algorithm automates the development of the fuzzy system, and makes the method easy to use for problems involving a large number of measurements, damage locations and sizes; such problems being typical of SHM. The ideas behind fuzzy logic, genetic algorithms and genetic fuzzy systems are also explained. The functionality of the genetic fuzzy system architecture is elucidated within a case-study framework, covering: • SHM of beams; • SHM of composite tubes; and • SHM of helicopter rotor blades. Structural Health Monitoring Using Genetic Fuzzy Systems will be useful for aerospace, civil and mechanical engineers working with structures and structured components. It will also be useful for computer scientists and applied mathematicians interested in the application of genetic fuzzy systems to engineering problems.

Foundations Of Generic Optimization

Foundations of Generic Optimization PDF Book Detail:
Author: R. Lowen
Publisher: Springer Science & Business Media
ISBN: 1402066686
Size: 62.81 MB
Format: PDF, Kindle
Category : Mathematics
Languages : en
Pages : 458
View: 5382

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Book Description: 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.

Neural Networks Fuzzy Logic And Genetic Algorithm

NEURAL NETWORKS  FUZZY LOGIC AND GENETIC ALGORITHM PDF Book Detail:
Author: S. RAJASEKARAN
Publisher: PHI Learning Pvt. Ltd.
ISBN: 8120321863
Size: 39.47 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 456
View: 573

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Book Description: 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.

Machine Learning

Machine Learning PDF Book Detail:
Author: Hojjat Adeli
Publisher: John Wiley & Sons Incorporated
ISBN:
Size: 42.74 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 211
View: 1163

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Book Description: This is the only book to apply neural nets, genetic algorithms, and fuzzy set theory to the fast growing field of machine learning. Placing particular emphasis on neural networks, it explores how to integrate them with other technologies to improve their performance. Examples are included for each system discussed.

Neural Networks Fuzzy Systems And Evolutionary Algorithms Synthesis And Applications

NEURAL NETWORKS  FUZZY SYSTEMS AND EVOLUTIONARY ALGORITHMS   SYNTHESIS AND APPLICATIONS PDF Book Detail:
Author: S. RAJASEKARAN
Publisher: PHI Learning Pvt. Ltd.
ISBN: 812035334X
Size: 46.67 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 576
View: 2090

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Book Description: 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.

Hybrid Information Systems

Hybrid Information Systems PDF Book Detail:
Author: Ajith Abraham
Publisher: Springer Science & Business Media
ISBN: 3790817821
Size: 47.37 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 734
View: 7642

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Book Description: Hybrid intelligent systems are becoming a very important problem-solving methodology affecting researchers and practitioners in areas ranging from science and technology to business and commerce. This volume focuses on the hybridization of different soft computing technologies and their interactions with hard computing techniques, other intelligent computing frameworks, and agents. Topics covered include: genetic-neurocomputing, neuro-fuzzy systems, genetic-fuzzy systems, genetic-fuzzy neurocomputing, hybrid optimization techniques, interaction with intelligent agents, fusion of soft computing and hard computing techniques, other intelligent systems and hybrid systems applications. The different contributions were presented at the first international workshop on hybrid intelligent systems (HIS1) in Adelaide, Australia.