Computational Intelligence in Reliability Engineering
New Metaheuristics, Neural and Fuzzy Techniques in Reliability
Series: Studies in Computational Intelligence; 40;
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Product details:
- Edition number 2007
- Publisher Springer Berlin Heidelberg
- Date of Publication 25 October 2006
- Number of Volumes 1 pieces, Book
- ISBN 9783540373711
- Binding Hardback
- No. of pages413 pages
- Size 235x155 mm
- Weight 805 g
- Language English
- Illustrations XIV, 413 p. Tables, black & white 0
Categories
Long description:
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.
MoreTable of Contents:
The Ant Colony Paradigm for Reliable Systems Design.- Modified Great Deluge Algorithm versus Other Metaheuristics in Reliability Optimization.- Applications of the Cross-Entropy Method in Reliability.- Particle Swarm Optimization in Reliability Engineering.- Cellular Automata and Monte Carlo Simulation for Network Reliability and Availability Assessment.- Network Reliability Assessment through Empirical Models using a Machine Learning Approach.- Neural Networks for Reliability-Based Optimal Design.- Software Reliability Predictions using Artificial Neural Networks.- Computation Intelligence in Online Reliability Monitoring.- Imprecise Reliability: An Introductory Overview.- Posbist Reliability Theory for Coherent Systems.- Analyzing Fuzzy System Reliability Based on the Vague Set Theory.- Fuzzy Sets in the Evaluation of Reliability.- Grey Differential Equation GM(1,1) Models in Repairable System Modeling.
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