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.
Download or read book Soft Computing In Systems And Control Technology written by Spyros Tzafestas and published by World Scientific. This book was released on 1999-05-21 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing is a branch of computing which, unlike hard computing, can deal with uncertain, imprecise and inexact data. The three constituents of soft computing are fuzzy-logic-based computing, neurocomputing, and genetic algorithms. Fuzzy logic contributes the capability of approximate reasoning, neurocomputing offers function approximation and learning capabilities, and genetic algorithms provide a methodology for systematic random search and optimization. These three capabilities are combined in a complementary and synergetic fashion.This book presents a cohesive set of contributions dealing with important issues and applications of soft computing in systems and control technology. The contributions include state-of-the-art material, mathematical developments, fresh results, and how-to-do issues. Among the problems studied via neural, fuzzy, neurofuzzy and genetic methodologies are: data fusion, reinforcement learning, approximation properties, multichannel imaging, signal processing, system optimization, gaming, and several forms of control.The book can serve as a reference for researchers and practitioners in the field. Readers can find in it a large amount of useful and timely information, and thus save considerable effort in searching for other scattered literature.
Download or read book Intelligent Hybrid Systems written by Da Ruan and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms is an organized edited collection of contributed chapters covering basic principles, methodologies, and applications of fuzzy systems, neural networks and genetic algorithms. All chapters are original contributions by leading researchers written exclusively for this volume. This book reviews important concepts and models, and focuses on specific methodologies common to fuzzy systems, neural networks and evolutionary computation. The emphasis is on development of cooperative models of hybrid systems. Included are applications related to intelligent data analysis, process analysis, intelligent adaptive information systems, systems identification, nonlinear systems, power and water system design, and many others. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms provides researchers and engineers with up-to-date coverage of new results, methodologies and applications for building intelligent systems capable of solving large-scale problems.
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.
Download or read book Computational Intelligence written by Christine L. Mumford and published by Springer Science & Business Media. This book was released on 2009-07-21 with total page 726 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about synergy in computational intelligence (CI). It is a c- lection of chapters that covers a rich and diverse variety of computer-based techniques, all involving some aspect of computational intelligence, but each one taking a somewhat pragmatic view. Many complex problems in the real world require the application of some form of what we loosely call “intel- gence”fortheirsolution. Fewcanbesolvedbythenaiveapplicationofasingle technique, however good it is. Authors in this collection recognize the li- tations of individual paradigms, and propose some practical and novel ways in which di?erent CI techniques can be combined with each other, or with more traditional computational techniques, to produce powerful probl- solving environments which exhibit synergy, i. e. , systems in which the whole 1 is greater than the sum of the parts . Computational intelligence is a relatively new term, and there is some d- agreement as to its precise de?nition. Some practitioners limit its scope to schemes involving evolutionary algorithms, neural networks, fuzzy logic, or hybrids of these. For others, the de?nition is a little more ?exible, and will include paradigms such as Bayesian belief networks, multi-agent systems, case-based reasoning and so on. Generally, the term has a similar meaning to the well-known phrase “Arti?cial Intelligence” (AI), although CI is p- ceived moreas a “bottom up” approachfrom which intelligent behaviour can emerge,whereasAItendstobestudiedfromthe“topdown”,andderivefrom pondering upon the “meaning of intelligence”. (These and other key issues will be discussed in more detail in Chapter 1.
Download or read book Neuro fuzzy Pattern Recognition written by Horst Bunke and published by World Scientific. This book was released on 2000 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks and fuzzy techniques are among the most promising approaches to pattern recognition. Neuro-fuzzy systems aim at combining the advantages of the two paradigms. This book is a collection of papers describing state-of-the-art work in this emerging field. It covers topics such as feature selection, classification, classifier training, and clustering. Also included are applications of neuro-fuzzy systems in speech recognition, land mine detection, medical image analysis, and autonomous vehicle control. The intended audience includes graduate students in computer science and related fields, as well as researchers at academic institutions and in industry.
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:
Download or read book Genetic Algorithms and Fuzzy Logic Systems written by Elie Sanchez and published by World Scientific. This book was released on 1997 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Hybrid Intelligent Systems written by Larry R. Medsker and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hybrid Intelligent Systems summarizes the strengths and weaknesses of five intelligent technologies: fuzzy logic, genetic algorithms, case-based reasoning, neural networks and expert systems, reviewing the status and significance of research into their integration. Engineering and scientific examples and case studies are used to illustrate principles and application development techniques. The reader will gain a clear idea of the current status of hybrid intelligent systems and discover how to choose and develop appropriate applications. The book is based on a thorough literature search of recent publications on research and development in hybrid intelligent systems; the resulting 50-page reference section of the book is invaluable. The book starts with a summary of the five major intelligent technologies and of the issues in and current status of research into them. Each subsequent chapter presents a detailed discussion of a different combination of intelligent technologies, along with examples and case studies. Four chapters contain detailed case studies of working hybrid systems. The book enables the reader to: Describe the important concepts, strengths and limitations of each technology; Recognize and analyze potential problems with the application of hybrid systems; Choose appropriate hybrid intelligent solutions; Understand how applications are designed with any of the approaches covered; Choose appropriate commercial development shells or tools. An invaluable reference source for those who wish to apply intelligent systems techniques to their own problems.
Download or read book Foundations of Neural Networks Fuzzy Systems and Knowledge Engineering written by Nikola K. Kasabov and published by Marcel Alencar. This book was released on 1996 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Artificial Intelligence Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-12-12 with total page 3048 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ongoing advancements in modern technology have led to significant developments in artificial intelligence. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Artificial Intelligence: Concepts, Methodologies, Tools, and Applications provides a comprehensive overview of the latest breakthroughs and recent progress in artificial intelligence. Highlighting relevant technologies, uses, and techniques across various industries and settings, this publication is a pivotal reference source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of artificial intelligence.
Download or read book Compensatory Genetic Fuzzy Neural Networks and Their Applications written by Yanqing Zhang and published by World Scientific. This book was released on 1998-08-22 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Contents:Fuzzy Compensation PrinciplesNormal Fuzzy Reasoning MethodologyCompensatory Genetic Fuzzy Neural NetworksFuzzy Knowledge Rediscovery in Fuzzy Rule BasesFuzzy Cart-Pole Balancing Control SystemsFuzzy Knowledge Compression and ExpansionHighly Nonlinear System Modeling and PredictionFuzzy Moves in Fuzzy GamesGenetic Neuro-Fuzzy Pattern RecognitionConstructive Approach to Modeling Fuzzy Systems Readership: Graduate students, researchers and experts in fuzzy logic, neural networks and genetic algorithms, and their applications. Keywords:Neural Networks;Fuzzy Logic;Genetic Algorithms;Evolutionary Computation;Granular Computing;Pattern Recognition;Data Mining;Knowledge Discovery;Nonlinear System Modeling;Game Theory;Control;Uncertainty Management;Decision Making;Compensatory Genetic Fuzzy Neural Networks
Download or read book Machine Learning written by Hojjat Adeli and published by . This book was released on 1995 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Foundations of Generic Optimization written by R. Lowen and published by Springer Science & Business Media. This book was released on 2007-10-27 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Advances in Fuzzy Logic Neural Networks and Genetic Algorithms written by Takeshi Furuhashi and published by . This book was released on 2014-01-15 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hybrid Information Systems written by Ajith Abraham and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Hybrid Information Systems written by Ajith Abraham and published by Springer Science & Business Media. This book was released on 2002-08-06 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
