Computational Intelligence in Reliability Engineering

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.

Presents applications of different metaheuristics (ant colony optimization, great deluge algorithm, cross-entropy method and particle swarm optimization) in reliability engineering Includes chapters devoted to cellular automata and support vector machines and different applications of artificial neural networks Describes different aspects of imprecise reliability and applications of fuzzy and vague set theory Includes supplementary material: sn.pub/extras

Autorentext
Dr. Gregory Levitin is an 'engineer-expert' in the Reliability and Equipment Department of the R and D Division of the Israel Electric Corporation and an adjunct senior lecturer at Technion, the Israel Institute of Technology. He has held these posts since 1993. He is considered to be an authoritative and experienced researcher in reliability and optimization. In addition to being a senior member of the IEEE, Dr. Levitin is also a member on the editorial board of the journal Reliability Engineering and System Safety. In 2000, Dr. Levitin was awarded a prize in the London Electricity Innovation Challenge. He has also been the organizer of special sessions on multi-state reliability at the Mathematic Methods in Reliability conferences in 2002 and 2004.

Klappentext

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.

Inhalt
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.