Neural networks, fuzzy systems, and evolutionary algorithms: synthesis and applications

By: Rajasekaran, S [Author] | Pai, G. A. Vijayalakshmi [Co-Author ]Material type: Text

TextLanguage: English Publication details: Delhi: PHIL, 2017. Edition: 2nd edDescription: xvi,552p.; 21cmsISBN: 9788120353343Subject(s): Soft computing | Fuzzy system | Evolutionary algorithmDDC classification: 006.3 S63, 2

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Books	Dr. S. R. Ranganathan Library General Stacks		006.3 R16, 2 (Browse shelf(Opens below))	1	Available	1523
Books	Dr. S. R. Ranganathan Library General Stacks		006.3 R16, 2:1 (Browse shelf(Opens below))	2	Available	1524
Books	Dr. S. R. Ranganathan Library General Stacks		006.3 R16, 2:2 (Browse shelf(Opens below))	3	Available	1801
Books	Dr. S. R. Ranganathan Library General Stacks		006.3 S16, 2:3 (Browse shelf(Opens below))	4	Available	1802
Reference	Dr. S. R. Ranganathan Library Reference	Reference	006.3 S63, 2:4 (Browse shelf(Opens below))	5	Not For Loan	1803

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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. New to the Second Edition
• New chapters on Extreme Learning Machine, Type-2 Fuzzy Sets, Evolution Strategies, Differential Evolution and Evolutionary Extreme Learning Machine.
• Revised chapters on Introduction to Artificial Intelligence Systems, Fuzzy Set Theory and Integration of Neural Networks, Fuzzy Set Theories and Evolutionary Algorithms.