Soft Computing
Soft Computing

Author: D. K. Pratihar

Publisher: Alpha Science International, Limited

Published: 2015-06-30

Total Pages: 296

ISBN-13: 9781783322053

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Soft Computing starts with an introduction to soft computing, a family consists of many members, namely genetic algorithms (GAs), fuzzy logic (FL), neural networks (NNs), and others. To realize the need for a non-traditional optimization tool like GA, one chapter is devoted to explain the principle of traditional optimization. The working cycle of a GA is explained in detail. The mechanisms of some specialized GAs are then discussed with some appropriate examples. The working principles of some other non-traditional optimization tools like simulated annealing (SA) and particle swarm optimization (PSO) are discussed in detail. Multi-objective optimization has been dealt in a separate chapter, where the working principles of a few approaches are explained. Fuzzy sets are introduced before explaining the principle of fuzzy reasoning and clustering. The fundamentals of NNs are presented, prior to the discussion on various forms of NN. The combined techniques, such as GA-FL, GA-NN, NN-FL and GA-FL-NN are then explained, and the last chapter deals with the applications of soft computing in two different fields of research. It has been written to fulfill the requirements of a large number of readers belonging to various disciplines of engineering and general sciences. The algorithms are discussed with a number of solved numerical examples. It will be very much helpful to the students, scientists and practicing engineers.

PRINCIPLES OF SOFT COMPUTING (With CD )
PRINCIPLES OF SOFT COMPUTING (With CD )

Author: S.N.Sivanandam & S.N.Deepa

Publisher: John Wiley & Sons

Published: 2007-06

Total Pages: 768

ISBN-13: 9788126510757

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Market_Desc: · B. Tech (UG) students of CSE, IT, ECE· College Libraries· Research Scholars· Operational Research· Management Sector Special Features: Dr. S. N. Sivanandam has published 12 books· He has delivered around 150 special lectures of different specialization in Summer/Winter school and also in various Engineering colleges· He has guided and co guided 30 PhD research works and at present 9 PhD research scholars are working under him· The total number of technical publications in International/National Journals/Conferences is around 700· He has also received Certificate of Merit 2005-2006 for his paper from The Institution of Engineers (India)· He has chaired 7 International Conferences and 30 National Conferences. He is a member of various professional bodies like IE (India), ISTE, CSI, ACS and SSI. He is a technical advisor for various reputed industries and engineering institutions· His research areas include Modeling and Simulation, Neural Networks, Fuzzy Systems and Genetic Algorithm, Pattern Recognition, Multidimensional system analysis, Linear and Nonlinear control system, Signal and Image processing, Control System, Power system, Numerical methods, Parallel Computing, Data Mining and Database Security About The Book: This book is meant for a wide range of readers who wish to learn the basic concepts of soft computing. It can also be helpful for programmers, researchers and management experts who use soft computing techniques. The basic concepts of soft computing are dealt in detail with the relevant information and knowledge available for understanding the computing process. The various neural network concepts are explained with examples, highlighting the difference between various architectures. Fuzzy logic techniques have been clearly dealt with suitable examples. Genetic algorithm operators and the various classifications have been discussed in lucid manner, so that a beginner can understand the concepts with minimal effort.

Soft Computing
Soft Computing

Author: Dilip Kumar Pratihar

Publisher: Alpha Science International, Limited

Published: 2014

Total Pages: 0

ISBN-13: 9781842658635

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SOFT COMPUTING: Fundamentals and Applications starts with an introduction to soft computing, a family consists of many members, namely Genetic Algorithms (GAs), Fuzzy Logic (FL), Neural Networks (NNs), and others. To realize the need for a non-traditional optimization tool like GA, one chapter is devoted to explain the principle of traditional optimization. The working cycle of a GA is explained in detail. The mechanisms of some specialized GAs are then discussed with some appropriate examples. The working principles of some other non-traditional optimization tools like Simulated Annealing (SA) and Particle Swarm Optimization (PSO) are discussed in detail. Multi-objective optimization has been dealt in a separate chapter, where the working principles of a few approaches are explained. Fuzzy sets are introduced before explaining the principle of fuzzy reasoning and clustering. The fundamentals of NNs are presented, prior to the discussion on various forms of NN. The combined techniques, such as GA-FL, GA-NN, NN-FL and GA-FL-NN are then explained, and the last chapter deals with the applications of soft computing in two different fields of research. It has been written to fulfill the requirements of a large number of readers belonging to various disciplines of engineering and general sciences. The algorithms are discussed with a number of solved numerical examples. It will be very much helpful to the students, scientists and practicing engineers.

FUNDAMENTAL OF SOFT COMPUTING
FUNDAMENTAL OF SOFT COMPUTING

Author: Kuntal Barua/Prof Prasun Chakrabarti

Publisher: BPB Publications

Published: 2018-06-01

Total Pages: 256

ISBN-13: 9387284778

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Description:This book is going to be the first well organized book for soft computing, including all the three major constituents or aspect of soft computing (neural networks, fuzzy logic and evolutionary computation), and hopefully will be proved beneficial for both kind of people; those striving to gain knowledge and those striving to score grades. The book is comprised of each and every topic of soft computing is a vast field of artificial intelligence with very much exploration to real time problems, especially regarding the quench of decision making and automation in the leading AI industries.Key Features:Comprehensive coverage of various aspects of soft computing concepts.Artificial intelligence, Neuro computing, Fuzzy logic Evolutionary computation.Strictly in accordance for the syllabus coverd under UG, PG, and Doctoral courses. (B.E. / B. Tech./ MCA/ M. Tech/ Research Scholars)Simple language, crystal clear approach, straight forward comprehensible presentation.The concepts are duly supported by several examples.Important question papers for every chapters.Table of contents:Chapter 1: Introduction to Neuro-computingChapter 2: Training the Neural networksChapter 3: The unsupervised networksChapter 4: The fuzzy logicChapter 5: The Evolutionary computationChapter 6: Few Auxiliary algorithms

Fundamentals of the Fuzzy Logic-Based Generalized Theory of Decisions
Fundamentals of the Fuzzy Logic-Based Generalized Theory of Decisions

Author: Rafik Aziz Aliev

Publisher: Springer

Published: 2013-01-12

Total Pages: 332

ISBN-13: 3642348955

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Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision making has a long history and arose also in Keynes’s analysis of uncertainty. There is a need for further generalization – a move to decision theories with perception-based imperfect information described in NL. The languages of new decision models for human-centric systems should be not languages based on binary logic but human-centric computational schemes able to operate on NL-described information. Development of new theories is now possible due to an increased computational power of information processing systems which allows for computations with imperfect information, particularly, imprecise and partially true information, which are much more complex than computations over numbers and probabilities. The monograph exposes the foundations of a new decision theory with imperfect decision-relevant information on environment and a decision maker’s behavior. This theory is based on the synthesis of the fuzzy sets theory with perception-based information and the probability theory. The book is self containing and represents in a systematic way the decision theory with imperfect information into the educational systems. The book will be helpful for teachers and students of universities and colleges, for managers and specialists from various fields of business and economics, production and social sphere.

Fundamentals of Soft Computing and Intelligent System
Fundamentals of Soft Computing and Intelligent System

Author: Padam Gulwani

Publisher:

Published: 2012-01-30

Total Pages: 0

ISBN-13: 9789381141731

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Provides the basic concepts and engineering applications of soft computing. It includes the basics of soft computing, the use, applications, advantages and disadvantages of neural networks, the basic concepts of supervised learning and the advantages of unsupervised learning and genetic algorithms and fuzzy logic.

Intelligent Control Systems Using Soft Computing Methodologies
Intelligent Control Systems Using Soft Computing Methodologies

Author: Ali Zilouchian

Publisher: CRC Press

Published: 2001-03-27

Total Pages: 504

ISBN-13: 1420058142

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In recent years, intelligent control has emerged as one of the most active and fruitful areas of research and development. Until now, however, there has been no comprehensive text that explores the subject with focus on the design and analysis of biological and industrial applications. Intelligent Control Systems Using Soft Computing Methodologies does all that and more. Beginning with an overview of intelligent control methodologies, the contributors present the fundamentals of neural networks, supervised and unsupervised learning, and recurrent networks. They address various implementation issues, then explore design and verification of neural networks for a variety of applications, including medicine, biology, digital signal processing, object recognition, computer networking, desalination technology, and oil refinery and chemical processes. The focus then shifts to fuzzy logic, with a review of the fundamental and theoretical aspects, discussion of implementation issues, and examples of applications, including control of autonomous underwater vehicles, navigation of space vehicles, image processing, robotics, and energy management systems. The book concludes with the integration of genetic algorithms into the paradigm of soft computing methodologies, including several more industrial examples, implementation issues, and open problems and open problems related to intelligent control technology. Suitable as a textbook or a reference, Intelligent Control Systems explores recent advances in the field from both the theoretical and the practical viewpoints. It also integrates intelligent control design methodologies to give designers a set of flexible, robust controllers and provide students with a tool for solving the examples and exercises within the book.

NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM
NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM

Author: S. RAJASEKARAN

Publisher: PHI Learning Pvt. Ltd.

Published: 2003-01-01

Total Pages: 459

ISBN-13: 8120321863

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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.

Fundamentals of the New Artificial Intelligence
Fundamentals of the New Artificial Intelligence

Author: Toshinori Munakata

Publisher: Springer Science & Business Media

Published: 2008-01-01

Total Pages: 266

ISBN-13: 1846288398

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The book covers the most essential and widely employed material in each area, particularly the material important for real-world applications. Our goal is not to cover every latest progress in the fields, nor to discuss every detail of various techniques that have been developed. New sections/subsections added in this edition are: Simulated Annealing (Section 3.7), Boltzmann Machines (Section 3.8) and Extended Fuzzy if-then Rules Tables (Sub-section 5.5.3). Also, numerous changes and typographical corrections have been made throughout the manuscript. The Preface to the first edition follows. General scope of the book Artificial intelligence (AI) as a field has undergone rapid growth in diversification and practicality. For the past few decades, the repertoire of AI techniques has evolved and expanded. Scores of newer fields have been added to the traditional symbolic AI. Symbolic AI covers areas such as knowledge-based systems, logical reasoning, symbolic machine learning, search techniques, and natural language processing. The newer fields include neural networks, genetic algorithms or evolutionary computing, fuzzy systems, rough set theory, and chaotic systems.

High Performance Programming for Soft Computing
High Performance Programming for Soft Computing

Author: Oscar Humberto Montiel Ross

Publisher: CRC Press

Published: 2014-02-04

Total Pages: 378

ISBN-13: 146658601X

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This book examines the present and future of soft computer techniques. It explains how to use the latest technological tools, such as multicore processors and graphics processing units, to implement highly efficient intelligent system methods using a general purpose computer.