Neural Networks, Fuzzy Systems and Evolutionary Algorithms: Synthesis and Applications - Softcover

S. Rajasekaran (author) & G.A. Vijayalakshmi Pai (author)

9788120353343: Neural Networks, Fuzzy Systems and Evolutionary Algorithms: Synthesis and Applications

Softcover

ISBN 10: 812035334X ISBN 13: 9788120353343

Publisher: PHI Learning, 2017

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The second edition of the 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.

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About the Author

S. Rajasekaran, D.Sc. (Civil Engineering) FNAE, is Visiting Professor, Department of Civil Engineering, PSG College of Technology, Coimbatore. He has 50 years of teaching and research experience and published more than 300 research papers in international and national journals. He was Alexander von Humboldt Fellow and recipient of several awards such as AICTE Award for Outstanding Academic and AICTE Award for Outstanding Researcher. His areas of special interest include Structural Engineering, Finite Element Analysis and Application of Soft Computing to Structural Engineering, Structural Dynamics and Stability of Structures.G.A. Vijayalakshmi PAI, Ph.D., SMIEEE, is an Associate Professor, Department of Computer Applications, PSG College of Technology, Coimbatore. Her research interests span the fields of Computational Intelligence, Computational Finance, Machine Learning and Pattern Recognition. She has investigated many research projects in the field of Computational Intelligence and its applications, funded by government agencies. She was the recipient of the AICTE Career Award for Young Teachers, 2001-a National Award given to young talented teachers who have established competence in their area of specialization, by the All India Council of Technical Education, New Delhi, India.

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