Neuro Fuzzy And Soft Computing

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Neuro-fuzzy and Soft Computing

Jyh-Shing Roger Jang,Chuen-Tsai Sun,Eiji Mizutani
Neuro fuzzy and Soft Computing Book PDF

Author : Jyh-Shing Roger Jang,Chuen-Tsai Sun,Eiji Mizutani
Publisher : Pearson Education
Page : 658 pages
File Size : 55,5 Mb
Release : 1997
Category : Computers
ISBN : UOM:39015038144864

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Neuro-fuzzy and Soft Computing by Jyh-Shing Roger Jang,Chuen-Tsai Sun,Eiji Mizutani Pdf

Neuro-Fuzzy and Soft Computing provides the first comprehensive treatment of the constituent methodologies underlying neuro-fuzzy and soft computing, an evolving branch of computational intelligence. The constituent methodologies include fuzzy set theory, neural networks, data clustering techniques, and several stochastic optimization methods that do not require gradient information. In particular, the authors put equal emphasis on theoretical aspects of covered methodologies, as well as empirical observations and verifications of various applications in practice. The book is well suited for use as a text for courses on computational intelligence and as a single reference source for this emerging field. To help readers understand the material the presentation includes more than 50 examples, more than 150 exercises, over 300 illustrations, and more than 150 Matlab scripts. In addition, Matlab is utilized to visualize the processes of fuzzy reasoning, neural-network learning, neuro-fuzzy integration and training, and gradient-free optimization (such as genetic algorithms, simulated annealing, random search, and downhill Simplex method). The presentation also makes use of SIMULINK for neuro-fuzzy control system simulations. All Matlab scripts used in the book are available on the free companion software disk that may be ordered by using the enclosed reply card. The book also contains an "Internet Resource Page" to point the reader to on-line neuro-fuzzy and soft computing home pages, publications, public-domain software, research institutes, news groups, etc. All the HTTP and FTP addresses are available as a bookmark file on the companion software disk.

Neuro-Fuzzy Pattern Recognition

Sankar K. Pal,Sushmita Mitra
Neuro Fuzzy Pattern Recognition Book PDF

Author : Sankar K. Pal,Sushmita Mitra
Publisher : Wiley-Interscience
Page : 418 pages
File Size : 46,5 Mb
Release : 1999
Category : Computers
ISBN : UOM:39015054399988

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Neuro-Fuzzy Pattern Recognition by Sankar K. Pal,Sushmita Mitra Pdf

The neuro-fuzzy approach to pattern recognition-a unique overview Recent years have seen a surge of interest in neuro-fuzzy computing, which combines fuzzy logic, neural networks, and soft computing techniques. This book focuses on the application of this new tool to the rapidly evolving area of pattern recognition. Written by two leaders in neural networks and soft computing research, this landmark work presents a unified, comprehensive treatment of the state of the art in the field. The authors consolidate a wealth of information previously cattered in disparate articles, journals, and edited volumes, explaining both the theory of neuro-fuzzy computing and the latest methodologies for performing different pattern recognition tasks in the neuro-fuzzy network-classification, feature evaluation, rule generation, knowledge extraction, and hybridization. Special emphasis is given to the integration of neuro-fuzzy methods with rough sets and genetic algorithms (GAs) to ensure more efficient recognition systems. Clear, concise, and fully referenced, Neuro-Fuzzy Pattern Recognition features extensive examples and highlights key applications in speech, machine learning, medicine, and forensic science. It is an extremely useful resource for scientists and engineers in laboratories and industry as well as for anyone seeking up-to-date information on the advantages of neuro-fuzzy pattern recognition in new computer technologies.

Introduction to Neuro-Fuzzy Systems

Robert Fuller
Introduction to Neuro Fuzzy Systems Book PDF

Author : Robert Fuller
Publisher : Springer Science & Business Media
Page : 300 pages
File Size : 54,9 Mb
Release : 2013-06-05
Category : Computers
ISBN : 9783790818529

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Introduction to Neuro-Fuzzy Systems by Robert Fuller Pdf

Fuzzy sets were introduced by Zadeh (1965) as a means of representing and manipulating data that was not precise, but rather fuzzy. Fuzzy logic pro vides an inference morphology that enables approximate human reasoning capabilities to be applied to knowledge-based systems. The theory of fuzzy logic provides a mathematical strength to capture the uncertainties associ ated with human cognitive processes, such as thinking and reasoning. The conventional approaches to knowledge representation lack the means for rep resentating the meaning of fuzzy concepts. As a consequence, the approaches based on first order logic and classical probablity theory do not provide an appropriate conceptual framework for dealing with the representation of com monsense knowledge, since such knowledge is by its nature both lexically imprecise and noncategorical. The developement of fuzzy logic was motivated in large measure by the need for a conceptual framework which can address the issue of uncertainty and lexical imprecision. Some of the essential characteristics of fuzzy logic relate to the following [242]. • In fuzzy logic, exact reasoning is viewed as a limiting case of ap proximate reasoning. • In fuzzy logic, everything is a matter of degree. • In fuzzy logic, knowledge is interpreted a collection of elastic or, equivalently, fuzzy constraint on a collection of variables. • Inference is viewed as a process of propagation of elastic con straints. • Any logical system can be fuzzified. There are two main characteristics of fuzzy systems that give them better performance für specific applications.

Neuro-Fuzzy Architectures and Hybrid Learning

Danuta Rutkowska
Neuro Fuzzy Architectures and Hybrid Learning Book PDF

Author : Danuta Rutkowska
Publisher : Physica
Page : 292 pages
File Size : 48,6 Mb
Release : 2012-11-13
Category : Computers
ISBN : 9783790818024

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Neuro-Fuzzy Architectures and Hybrid Learning by Danuta Rutkowska Pdf

The advent of the computer age has set in motion a profound shift in our perception of science -its structure, its aims and its evolution. Traditionally, the principal domains of science were, and are, considered to be mathe matics, physics, chemistry, biology, astronomy and related disciplines. But today, and to an increasing extent, scientific progress is being driven by a quest for machine intelligence - for systems which possess a high MIQ (Machine IQ) and can perform a wide variety of physical and mental tasks with minimal human intervention. The role model for intelligent systems is the human mind. The influ ence of the human mind as a role model is clearly visible in the methodolo gies which have emerged, mainly during the past two decades, for the con ception, design and utilization of intelligent systems. At the center of these methodologies are fuzzy logic (FL); neurocomputing (NC); evolutionary computing (EC); probabilistic computing (PC); chaotic computing (CC); and machine learning (ML). Collectively, these methodologies constitute what is called soft computing (SC). In this perspective, soft computing is basically a coalition of methodologies which collectively provide a body of concepts and techniques for automation of reasoning and decision-making in an environment of imprecision, uncertainty and partial truth.

Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications

Okyay Kaynak,Lotfi A. Zadeh,Burhan Türksen,Imre J. Rudas
Computational Intelligence Soft Computing and Fuzzy Neuro Integration with Applications Book PDF

Author : Okyay Kaynak,Lotfi A. Zadeh,Burhan Türksen,Imre J. Rudas
Publisher : Springer Science & Business Media
Page : 552 pages
File Size : 54,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642589300

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Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration with Applications by Okyay Kaynak,Lotfi A. Zadeh,Burhan Türksen,Imre J. Rudas Pdf

Soft computing is a consortium of computing methodologies that provide a foundation for the conception, design, and deployment of intelligent systems and aims to formalize the human ability to make rational decisions in an environment of uncertainty and imprecision. This book is based on a NATO Advanced Study Institute held in 1996 on soft computing and its applications. The distinguished contributors consider the principal constituents of soft computing, namely fuzzy logic, neurocomputing, genetic computing, and probabilistic reasoning, the relations between them, and their fusion in industrial applications. Two areas emphasized in the book are how to achieve a synergistic combination of the main constituents of soft computing and how the combination can be used to achieve a high Machine Intelligence Quotient.

Neuro-Fuzzy Techniques for Intelligent Information Systems

Nikola K. Kasabov
Neuro Fuzzy Techniques for Intelligent Information Systems Book PDF

Author : Nikola K. Kasabov
Publisher : Physica
Page : 472 pages
File Size : 45,7 Mb
Release : 1999-03-29
Category : Business & Economics
ISBN : UVA:X004323696

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Neuro-Fuzzy Techniques for Intelligent Information Systems by Nikola K. Kasabov Pdf

This volume comprises selected chapters that cover contemporary issues of the development and the application of neuro-fuzzy techniques. Developing and using neural networks, fuzzy logic systems, genetic algorithms and statistical methods as separate techniques, or in their combination, have been research topics in several areas such as mathematics, engineering, computer science, physics, economics and finance. Here the latest results in the fields are presented from both theoretical and practical point of view. The volume has four main parts. Part one presents generic techniques and theoretical issues while part two, three and four deal with practically oriented models, systems and implementations.

Computational Intelligence Systems and Applications

Marian B. Gorzalczany
Computational Intelligence Systems and Applications Book PDF

Author : Marian B. Gorzalczany
Publisher : Physica
Page : 367 pages
File Size : 40,8 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783790818017

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Computational Intelligence Systems and Applications by Marian B. Gorzalczany Pdf

Traditional Artificial Intelligence (AI) systems adopted symbolic processing as their main paradigm. Symbolic AI systems have proved effective in handling problems characterized by exact and complete knowledge representation. Unfortunately, these systems have very little power in dealing with imprecise, uncertain and incomplete data and information which significantly contribute to the description of many real world problems, both physical systems and processes as well as mechanisms of decision making. Moreover, there are many situations where the expert domain knowledge (the basis for many symbolic AI systems) is not sufficient for the design of intelligent systems, due to incompleteness of the existing knowledge, problems caused by different biases of human experts, difficulties in forming rules, etc. In general, problem knowledge for solving a given problem can consist of an explicit knowledge (e.g., heuristic rules provided by a domain an implicit, hidden knowledge "buried" in past-experience expert) and numerical data. A study of huge amounts of these data (collected in databases) and the synthesizing of the knowledge "encoded" in them (also referred to as knowledge discovery in data or data mining), can significantly improve the performance of the intelligent systems designed.

Fuzzy and Neuro-Fuzzy Intelligent Systems

Ernest Czogala,Jacek Leski
Fuzzy and Neuro Fuzzy Intelligent Systems Book PDF

Author : Ernest Czogala,Jacek Leski
Publisher : Physica
Page : 207 pages
File Size : 49,5 Mb
Release : 2012-08-10
Category : Computers
ISBN : 9783790818536

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Fuzzy and Neuro-Fuzzy Intelligent Systems by Ernest Czogala,Jacek Leski Pdf

Intelligence systems. We perfonn routine tasks on a daily basis, as for example: • recognition of faces of persons (also faces not seen for many years), • identification of dangerous situations during car driving, • deciding to buy or sell stock, • reading hand-written symbols, • discriminating between vines made from Sauvignon Blanc, Syrah or Merlot grapes, and others. Human experts carry out the following: • diagnosing diseases, • localizing faults in electronic circuits, • optimal moves in chess games. It is possible to design artificial systems to replace or "duplicate" the human expert. There are many possible definitions of intelligence systems. One of them is that: an intelligence system is a system able to make decisions that would be regarded as intelligent ifthey were observed in humans. Intelligence systems adapt themselves using some example situations (inputs of a system) and their correct decisions (system's output). The system after this learning phase can make decisions automatically for future situations. This system can also perfonn tasks difficult or impossible to do for humans, as for example: compression of signals and digital channel equalization.

Soft Computing and Its Applications

Rafik Aziz ogly Aliev,R. R. Aliev
Soft Computing and Its Applications Book PDF

Author : Rafik Aziz ogly Aliev,R. R. Aliev
Publisher : World Scientific
Page : 470 pages
File Size : 55,6 Mb
Release : 2001
Category : Computers
ISBN : 9810247001

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Soft Computing and Its Applications by Rafik Aziz ogly Aliev,R. R. Aliev Pdf

The concept of soft computing is still in its initial stages of crystallization. Presently available books on soft computing are merely collections of chapters or articles about different aspects of the field. This book is the first to provide a systematic account of the major concepts and methodologies of soft computing, presenting a unified framework that makes the subject more accessible to students and practitioners. Particularly worthy of note is the inclusion of a wealth of information about neuro-fuzzy, neuro-genetic, fuzzy-genetic and neuro-fuzzy-genetic systems, with many illuminating applications and examples.

Fuzzy Systems and Soft Computing in Nuclear Engineering

Da Ruan
Fuzzy Systems and Soft Computing in Nuclear Engineering Book PDF

Author : Da Ruan
Publisher : Springer Science & Business Media
Page : 506 pages
File Size : 44,7 Mb
Release : 2000-01-14
Category : Business & Economics
ISBN : 379081251X

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Fuzzy Systems and Soft Computing in Nuclear Engineering by Da Ruan Pdf

This book is an organized edited collection of twenty-one contributed chapters covering nuclear engineering applications of fuzzy systems, neural networks, genetic algorithms and other soft computing techniques. All chapters are either updated review or original contributions by leading researchers written exclusively for this volume. The volume highlights the advantages of applying fuzzy systems and soft computing in nuclear engineering, which can be viewed as complementary to traditional methods. As a result, fuzzy sets and soft computing provide a powerful tool for solving intricate problems pertaining in nuclear engineering. Each chapter of the book is self-contained and also indicates the future research direction on this topic of applications of fuzzy systems and soft computing in nuclear engineering.

Deep Neuro-Fuzzy Systems with Python

Himanshu Singh,Yunis Ahmad Lone
Deep Neuro Fuzzy Systems with Python Book PDF

Author : Himanshu Singh,Yunis Ahmad Lone
Publisher : Apress
Page : 270 pages
File Size : 49,5 Mb
Release : 2019-11-30
Category : Computers
ISBN : 9781484253618

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Deep Neuro-Fuzzy Systems with Python by Himanshu Singh,Yunis Ahmad Lone Pdf

Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current world. This book simplifies the implementation of fuzzy logic and neural network concepts using Python. You’ll start by walking through the basics of fuzzy sets and relations, and how each member of the set has its own membership function values. You’ll also look at different architectures and models that have been developed, and how rules and reasoning have been defined to make the architectures possible. The book then provides a closer look at neural networks and related architectures, focusing on the various issues neural networks may encounter during training, and how different optimization methods can help you resolve them. In the last section of the book you’ll examine the integrations of fuzzy logics and neural networks, the adaptive neuro fuzzy Inference systems, and various approximations related to the same. You’ll review different types of deep neuro fuzzy classifiers, fuzzy neurons, and the adaptive learning capability of the neural networks. The book concludes by reviewing advanced neuro fuzzy models and applications. What You’ll Learn Understand fuzzy logic, membership functions, fuzzy relations, and fuzzy inferenceReview neural networks, back propagation, and optimizationWork with different architectures such as Takagi-Sugeno model, Hybrid model, genetic algorithms, and approximations Apply Python implementations of deep neuro fuzzy system Who This book Is For Data scientists and software engineers with a basic understanding of Machine Learning who want to expand into the hybrid applications of deep learning and fuzzy logic.

Fuzzy Logic and Soft Computing

Bernadette Bouchon-Meunier,Ronald R Yager,Lotfi A Zadeh
Fuzzy Logic and Soft Computing Book PDF

Author : Bernadette Bouchon-Meunier,Ronald R Yager,Lotfi A Zadeh
Publisher : World Scientific
Page : 508 pages
File Size : 53,9 Mb
Release : 1995-09-15
Category : Computers
ISBN : 9789814500081

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Fuzzy Logic and Soft Computing by Bernadette Bouchon-Meunier,Ronald R Yager,Lotfi A Zadeh Pdf

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. Contents:Fuzzy Logic and Genetic AlgorithmsLearningFuzzy and Hybrid SystemsDecision and Aggregation TechniquesFuzzy Logic in DatabasesFoundations of Fuzzy LogicApplications of Fuzzy Sets Readership: Researchers and computer scientists. keywords:

Fuzzy Systems Engineering

Nadia Nedjah,Luiza de Macedo Mourelle
Fuzzy Systems Engineering Book PDF

Author : Nadia Nedjah,Luiza de Macedo Mourelle
Publisher : Springer Science & Business Media
Page : 252 pages
File Size : 55,6 Mb
Release : 2005-05-20
Category : Computers
ISBN : 354025322X

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Fuzzy Systems Engineering by Nadia Nedjah,Luiza de Macedo Mourelle Pdf

This book is devoted to reporting innovative and significant progress in fuzzy system engineering. Given the maturation of fuzzy logic, this book is dedicated to exploring the recent breakthroughs in fuzziness and soft computing in favour of intelligent system engineering. This monograph presents novel developments of the fuzzy theory as well as interesting applications of the fuzzy logic exploiting the theory to engineer intelligent systems.

Soft Computing

Andrea Tettamanzi,Marco Tomassini
Soft Computing Book PDF

Author : Andrea Tettamanzi,Marco Tomassini
Publisher : Springer Science & Business Media
Page : 335 pages
File Size : 45,9 Mb
Release : 2013-04-17
Category : Mathematics
ISBN : 9783662043356

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Soft Computing by Andrea Tettamanzi,Marco Tomassini Pdf

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

Knowledge-Based Neurocomputing: A Fuzzy Logic Approach

Eyal Kolman,Michael Margaliot
Knowledge Based Neurocomputing A Fuzzy Logic Approach Book PDF

Author : Eyal Kolman,Michael Margaliot
Publisher : Springer
Page : 100 pages
File Size : 43,5 Mb
Release : 2008-10-18
Category : Computers
ISBN : 9783540880776

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Knowledge-Based Neurocomputing: A Fuzzy Logic Approach by Eyal Kolman,Michael Margaliot Pdf

In this monograph, the authors introduce a novel fuzzy rule-base, referred to as the Fuzzy All-permutations Rule-Base (FARB). They show that inferring the FARB, using standard tools from fuzzy logic theory, yields an input-output map that is mathematically equivalent to that of an artificial neural network. Conversely, every standard artificial neural network has an equivalent FARB. The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases and sub-symbolic artificial neural networks, and yields a new approach for knowledge-based neurocomputing in artificial neural networks.