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Computational Intelligence in Reliability Engineering : New Metaheuristics, Neural and Fuzzy Techniques in Reliability
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.
Computational Intelligence in Reliability Engineering : Evolutionary Techniques in Reliability Analysis and Optimization
This book covers the recent applications of computational intelligence techniques in reliability engineering. This volume contains a survey of the contributions made to the optimal reliability design literature in the resent years and chapters devoted to different applications of a genetic algorithm in reliability engineering and to combinations of this algorithm with other computational intelligence techniques. Genetic algorithms are one of the most widely used metaheuristics, inspired by the optimization procedure that exists in nature, the biological phenomenon of evolution.
MARE-WINT : New Materials and Reliability in Offshore Wind Turbine Technology
This book provides a holistic, interdisciplinary overview of offshore wind energy, and is a must-read for advanced researchers. Topics, from the design and analysis of future turbines, to the decommissioning of wind farms, are covered. The scope of the work ranges from analytical, numerical and experimental advancements in structural and fluid mechanics, to novel developments in risk, safety & reliability engineering for offshore wind. The core objective of the current work is to make offshore wind energy more competitive, by improving the reliability, and operations and maintenance (O&M) strategies of wind turbines.
Justifying the Dependability of Computer-based Systems : With Applications in Nuclear Engineering
The book also explores some of the more fundamental aspects of safety evaluation, such as the nature of models, arguments, evidence and documentation, and the ways to deal with different types of risk and uncertainty. Justifying the Dependability of Computer-based Systems will be of value to software, computer system, instrumentation and control engineers, and regulators working in industry sectors such as nuclear safety.
Advances in Mathematical and Statistical Modeling
Enrique Castillo is a leading figure in several mathematical, statistical, and engineering fields, having contributed seminal work in such areas as statistical modeling, extreme value analysis, multivariate distribution theory, Bayesian networks, neural networks, functional equations, artificial intelligence, linear algebra, optimization methods, numerical methods, reliability engineering, as well as sensitivity analysis and its applications. Organized to honor Castillo's significant contributions, this volume is an outgrowth of the International Conference on Mathematical and Statistical Modeling and covers recent advances in the field. Also presented are applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques.
Advanced Reliability Models and Maintenance Policies
Advanced Reliability Models and Maintenance Policies introduces partition and redundant problems within reliability models, and provides optimization techniques. The book also indicates how to perform maintenance in a finite time span and at failure detection, and to apply recovery techniques for computer systems.
