Computational Intelligence in Reliability Engineering
Evolutionary Techniques in Reliability Analysis and Optimization
Series: Studies in Computational Intelligence; 39;
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Product details:
- Edition number Softcover reprint of hardcover 1st ed. 2007
- Publisher Springer Berlin Heidelberg
- Date of Publication 19 November 2010
- Number of Volumes 1 pieces, Previously published in hardcover
- ISBN 9783642072185
- Binding Paperback
- See also 9783540373674
- No. of pages398 pages
- Size 235x155 mm
- Weight 629 g
- Language English
- Illustrations XIV, 398 p. Tables, black & white 0
Categories
Long description:
This two-volume book covers the recent applications of computational intel- 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, fuzzy logic, evolutionary computing, and their hybrids and derivatives. Many industries have benefited from adopting this technology. The increased number of patents and diverse range of products dev- 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 te- 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.
MoreTable of Contents:
Recent Advances in Optimal Reliability Allocation.- Multiobjective Metaheuristic Approaches to Reliability Optimization.- Genetic Algorithm Applications in Surveillance and Maintenance Optimization.- Genetic Algorithms and Monte Carlo Simulation for the Optimization of System Design and Operation.- New Evolutionary Methodologies for Integrated Safety System Design and Maintenance Optimization.- Optimal Redundancy Allocation of Multi-State Systems with Genetic Algorithms.- Intelligent Interactive Multiobjective Optimization of System Reliability.- Reliability Assessment of Composite Power Systems Using Genetic Algorithms.- Genetic Optimization of Multidimensional Technological Process Reliability.- Scheduling Multiple-version Programs on Multiple Processors.- Redundancy Optimization Problems with Uncertain Lifetimes.- Computational Intelligence Methods in Software Reliability Prediction.
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