Computational Intelligence in Reliability Engineering : New Metaheuristics, Neural and Fuzzy Techniques in Reliability / edited by Gregory Levitin.

Springer eBooks

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.

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.

Para consulta fuera de la UANL se requiere clave de acceso remoto.