Computational Intelligence in Reliability Engineering

ISBN 10: 3540373713 / ISBN 13: 9783540373711

Published by Springer, 2006

About this Item

pp. xiv + 413.

Seller Inventory # 7545181

Bibliographic Details

• Title: Computational Intelligence in Reliability Engineering
• Publisher: Springer
• Publication Date: 2006
• Language: English
• ISBN 10: 3540373713
• ISBN 13: 9783540373711
• Binding: Hardcover
• Condition: New

About this title

Synopsis

This two volume book covers the recent applications of computational intelli gence techniques in reliability engineering. Research in the area of computational intelligence is growing rapidly due to the many successful applications of these new techniques in very diverse problems. “Computational Intelligence” covers many fields such as neural networks, fu zzy logic, evolutionary computing, and their hybrids and derivatives. Many indus tries have benefited from adopting this technology. The increased number of patents and diverse range of products devel oped using computational intelligence methods is evidence of this fact. These techniques have attracted increasing attention in recent years for solving many complex problems. They are inspired by nature, biology, statistical tech niques, physics and neuroscience. They have been successfully applied in solving many complex problems where traditional problem solving methods have failed. The book aims to be a repository for the current and cutting edge applications of computational intelligent techniques in reliability analysis and optimization.

From the Back Cover

This volume contains chapters presenting applications of different metaheuristics (ant colony optimization, great deluge algorithm, cross-entropy method and particle swarm optimization) in reliability engineering. It also includes chapters devoted to cellular automata and support vector machines and different applications of artificial neural networks, a powerful adaptive technique that can be used for learning, prediction and optimization. Several chapters describe different aspects of imprecise reliability and applications of fuzzy and vague set theory.