Описание: Focuses on various computational intelligence (CI) methods that can be applied to improve the efficiency and effectiveness of aerospace design through numerical simulation. This book covers case studies and examples with industrial significance that help to make theory digestible for engineers and researchers without a computer science background.
Описание: Computational intelligence paradigms have attracted the growing interest of researchers, scientists, engineers and application engineers in a number of everyday applications. These applications are not limited to any particular field and include engineering, business, banking and consumer electronics. Computational intelligence paradigms include artificial intelligence, artificial neural networks, fuzzy systems and evolutionary computing. Artificial neural networks can mimic the biological information processing mechanism in a very limited sense. Evolutionary computing algorithms are used for optimisation applications, and fuzzy logic provides a basis for representing uncertain and imprecise knowledge. Practical Applications of Computational Intelligence Techniques contains twelve chapters providing actual application of these techniques in the real world. Such examples include, but are not limited to, intelligent household appliances, aerial spray models, industrial applications and medical diagnostics and practice. This book will be useful to researchers, practicing engineers/scientists and students, who are interested in developing practical applications in a computational intelligence environment.
Описание: 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.
Описание: Provides a basic illustration of some methods used in reliability and risk analysis for modelling the stochastic failure and repair behaviour of systems. This work offers an introduction to key issues of system reliability and risk analysis, like dependent failures and importance measures.
Описание: Gives a comprehensive description of the universal generating function technique and its applications in binary and multi-state system reliability analysis. This monograph is of interest to those interested in system reliability, performance analysis and optimization in industrial, electrical and nuclear engineering.
Описание: As our modern information-age society grows in complexity both in terms of embedded systems and applications, the problems and challenges in reliability
become ever more complex. Bringing together many of the leading experts in the field, this volume presents a broad picture of current research on system modeling and optimization in
reliability and its applications. The book comprises twenty-three chapters organized into four parts: Reliability Modeling, Software Quality Engineering, Software Reliability, and
Maintenance and Inspection Policies.
These sections cover a wide range of important topics, including system reliability modeling, optimization, software reliability and quality,
maintenance theory and inspection, reliability failure analysis, sampling plans and schemes, software development processes and improvement, stochastic process modeling, statistical
distributions and analysis, fault-tolerant performance, software measurements and cost effectiveness, queueing theory and applications, system availability, reliability of repairable
systems, testing sampling inspection, software capability maturity model, accelerated life modeling, statistical control, and HALT testing.
Описание: This practically oriented book presents a comprehensive, up-to-date description of multi-state system (MSS) reliability as a natural extension of classical binary-state reliability. It presents all essential theoretical achievements in the field.
Автор: Mohammad Modarres, Mark Kaminskiy and Vasiliy Kriv Название: Reliability Engineering and Risk Analysis ISBN: 0849392470 ISBN-13(EAN): 9780849392474 Издательство: Taylor&Francis Рейтинг: Цена: 7732 р. Наличие на складе: Поставка под заказ.
Описание: With a focus on reliability analysis, this text provides a practical and comprehensive overview of reliability and risk analysis techniques. It features topics including generalized renewal with applications, Bayesian estimation methods, and estimation of bounds of repairable unit reliability and availability.
Описание: Integrates reliability assessment and risk analysis into planning, design, and management. This book provides tools for designing safer, more reliable dams, storm sewer networks, water treatment plants, and pollution control systems. It demonstrates statistical and probability tools for solving a broad range of hydrosystem engineering problems.
Описание: This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this field.
Описание: A combination of theoretical treatment and real-world insight introduce the field of computational intelligence in this valuable reference. Topics include neural networks, frameworks for optimization, parallelization of algorithms, and more.
Описание: Unlike traditional computing, Computational Intelligence is tolerant of imprecise information, partial truth and uncertainty. This book presents a selected collection of contributions on a focused treatment of important elements of CI, centred on its key element: learning. All the contributors of this volume have direct bearing with this issue. From fundamentals to advanced systems as Multilayer Perceptron Artificial Neural Networks (ANN-MLP), Radial Basis Function Networks (RBF) and its relations with Fuzzy Sets and Support Vector Machines theory; and on to several critical applications in Engineering and Manufacturing. These are among applications where CI have excellent potential.This volume has specially taken Neural Networks, key elements of CI, to the next level. Both novice and expert readers can benefit from this timely addition to CI based literature. Towards that goal, the editors and the authors have made critical contributions and succeeded. They have paved the road for learning paradigms towards the solution of many real-world problems.
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