Reliability Engineering and Computational Intelligence
Reliability Engineering and Computational Intelligence

Author: Coen van Gulijk

Publisher: Springer Nature

Published: 2021-08-06

Total Pages: 307

ISBN-13: 3030745562

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Computational intelligence is rapidly becoming an essential part of reliability engineering. This book offers a wide spectrum of viewpoints on the merger of technologies. Leading scientists share their insights and progress on reliability engineering techniques, suitable mathematical methods, and practical applications. Thought-provoking ideas are embedded in a solid scientific basis that contribute to the development the emerging field. This book is for anyone working on the most fundamental paradigm-shift in resilience engineering in decades. Scientists benefit from this book by gaining insight in the latest in the merger of reliability engineering and computational intelligence. Businesses and (IT) suppliers can find inspiration for the future, and reliability engineers can use the book to move closer to the cutting edge of technology.

Computational Intelligence in Reliability Engineering
Computational Intelligence in Reliability Engineering

Author: Gregory Levitin

Publisher: Springer Science & Business Media

Published: 2006-10-26

Total Pages: 412

ISBN-13: 3540373675

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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 recent years. It also contains chapters devoted to different applications of a genetic algorithm in reliability engineering and to combinations of this algorithm with other computational intelligence techniques.

New Computational Methods in Power System Reliability
New Computational Methods in Power System Reliability

Author: David Elmakias

Publisher: Springer Science & Business Media

Published: 2008-07-07

Total Pages: 416

ISBN-13: 3540778101

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Power system reliability is the focus of intensive study due to its critical role in providing energy supply to modern society. This comprehensive book describes application of some new specific techniques: universal generating function method and its combination with Monte Carlo simulation and with random processes methods, Semi-Markov and Markov reward models and genetic algorithm. The book can be considered as complementary to power system reliability textbooks.

Computational Intelligence in Power Engineering
Computational Intelligence in Power Engineering

Author: Bijaya Ketan Panigrahi

Publisher: Springer Science & Business Media

Published: 2010-09-20

Total Pages: 385

ISBN-13: 3642140122

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This volume deals with different computational intelligence (CI) techniques for solving real world power industry problems. It will be extremely helpful for the researchers as well as the practicing engineers in the power industry.

Computational Intelligence Techniques and Their Applications to Software Engineering Problems
Computational Intelligence Techniques and Their Applications to Software Engineering Problems

Author: Ankita Bansal

Publisher: CRC Press

Published: 2020-09-27

Total Pages: 267

ISBN-13: 1000191923

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Computational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and much more. The concepts of expert systems, case-based reasoning, fuzzy logic, genetic algorithms, swarm computing, and rough sets are introduced with their applications in software engineering. The field of knowledge discovery is explored using neural networks and data mining techniques by determining the underlying and hidden patterns in software data sets. Aimed at graduate students and researchers in computer science engineering, software engineering, information technology, this book: Covers various aspects of in-depth solutions of software engineering problems using computational intelligence techniques Discusses the latest evolutionary approaches to preliminary theory of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to provide better and optimized solutions Illustrates applications including software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, and more Highlights swarm intelligence-based optimization solutions for software testing and reliability problems

Reliability Engineering and Computational Intelligence for Complex Systems
Reliability Engineering and Computational Intelligence for Complex Systems

Author: Coen van Gulijk

Publisher: Springer Nature

Published: 2023-09-23

Total Pages: 224

ISBN-13: 3031409973

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This book offers insight into the current issues of the merger between reliability engineering and computational intelligence. The intense development of information technology allows for designing more complex systems as well as creating more detailed models of real-world systems which forces traditional reliability engineering approaches based on Boolean algebra, probability theory, and statistics to embrace the world of data science. The works deal with methodological developments as well as applications in the development of safe and reliable systems in various kinds of distribution networks, in the development of highly reliable healthcare systems, in finding weaknesses in systems with the human factor, or in reliability analysis of large information systems and other software solutions. In this book, experts from various fields of reliability engineering and computational intelligence present their view on the risks, the opportunities and the synergy between reliability engineering and computational intelligence that have been developed separately but in recent years have found a way to each other. The topics addressed include the latest advances in computing technology to improve the real lives of millions of people by increasing safety and reliability of various types of real-life systems by increasing the availability of software services, reducing the accident rate of means of transport, developing high reliable patient-specific health care, or generally, save cost and increase efficiency in the work and living environment. Though this book, the reader has access to professionals and researchers in the fields of reliability engineering and computational intelligence that share their experience in merging the two as well as an insight into the latest methods, concerns and application domains.

Computational Intelligence in Sustainable Reliability Engineering
Computational Intelligence in Sustainable Reliability Engineering

Author: S. C. Malik

Publisher: John Wiley & Sons

Published: 2023-03-28

Total Pages: 356

ISBN-13: 1119865018

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COMPUTATIONAL INTELLIGENCE IN SUBSTAINABLE RELIABILITY ENGINEERING The book is a comprehensive guide on how to apply computational intelligence techniques for the optimization of sustainable materials and reliability engineering. This book focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in reliability engineering, material design, and manufacturing to ensure sustainability. Computational Intelligence in Sustainable Reliability Engineering unveils applications of different models of evolutionary algorithms in the field of optimization and solves the problems to help the manufacturing industries. Some special features of this book include a comprehensive guide for utilizing computational models for reliability engineering, state-of-the-art swarm intelligence methods for solving manufacturing processes and developing sustainable materials, high-quality and innovative research contributions, and a guide for applying computational optimization on reliability and maintainability theory. The book also includes dedicated case studies of real-life applications related to industrial optimizations. Audience Researchers, industry professionals, and post-graduate students in reliability engineering, manufacturing, materials, and design.

Computational Intelligence in Time Series Forecasting
Computational Intelligence in Time Series Forecasting

Author: Ajoy K. Palit

Publisher: Springer Science & Business Media

Published: 2006-01-04

Total Pages: 382

ISBN-13: 1846281849

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Foresight in an engineering business can make the difference between success and failure, and can be vital to the effective control of industrial systems. The authors of this book harness the power of intelligent technologies individually and in combination.

AI Techniques for Reliability Prediction for Electronic Components
AI Techniques for Reliability Prediction for Electronic Components

Author: Bhargava, Cherry

Publisher: IGI Global

Published: 2019-12-06

Total Pages: 330

ISBN-13: 1799814661

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In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.