Computational Intelligence in Reliability Engineering New Metaheuristics, Neural and Fuzzy Techniques in Reliability
Title:
Computational Intelligence in Reliability Engineering New Metaheuristics, Neural and Fuzzy Techniques in Reliability
Author:
Levitin, Gregory. editor.
ISBN:
9783540373728
Physical Description:
XIV, 413 p. online resource.
Series:
Studies in Computational Intelligence, 40
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.
Abstract:
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.
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Electronic Access:
http://dx.doi.org/10.1007/978-3-540-37372-8