Author: Coen van Gulijk
Publisher: Springer Nature
ISBN: 3030745562
Category : Technology & Engineering
Languages : en
Pages : 307
Book Description
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.
Reliability Engineering and Computational Intelligence
New Computational Methods in Power System Reliability
Author: David Elmakias
Publisher: Springer Science & Business Media
ISBN: 3540778101
Category : Mathematics
Languages : en
Pages : 416
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 3540778101
Category : Mathematics
Languages : en
Pages : 416
Book Description
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
Author: Bijaya Ketan Panigrahi
Publisher: Springer Science & Business Media
ISBN: 3642140122
Category : Computers
Languages : en
Pages : 385
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 3642140122
Category : Computers
Languages : en
Pages : 385
Book Description
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 in Time Series Forecasting
Author: Ajoy K. Palit
Publisher: Springer Science & Business Media
ISBN: 1846281849
Category : Computers
Languages : en
Pages : 382
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 1846281849
Category : Computers
Languages : en
Pages : 382
Book Description
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.
Computational Intelligence Techniques and Their Applications to Software Engineering Problems
Author: Ankita Bansal
Publisher: CRC Press
ISBN: 1000191923
Category : Computers
Languages : en
Pages : 267
Book Description
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
Publisher: CRC Press
ISBN: 1000191923
Category : Computers
Languages : en
Pages : 267
Book Description
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
Computational Intelligence in Sustainable Reliability Engineering
Author: S. C. Malik
Publisher: John Wiley & Sons
ISBN: 1119865018
Category : Technology & Engineering
Languages : en
Pages : 356
Book Description
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.
Publisher: John Wiley & Sons
ISBN: 1119865018
Category : Technology & Engineering
Languages : en
Pages : 356
Book Description
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.
Reliability and Risk Analysis in Engineering and Medicine
Author: Chandrasekhar Putcha
Publisher: Springer Nature
ISBN: 3030804542
Category : Technology & Engineering
Languages : en
Pages : 138
Book Description
This graduate textbook imparts the fundamentals of reliability and risk that can be connected mathematically and applied to problems in engineering and medical science and practice. The book is divided into eight chapters, the first three of which deal with basic fundamentals of probability theory and reliability methods. The fourth chapter illustrates simulation methods needed to solve complex problems. Chapters 5-7 explain reliability codes and system reliability (which uses the component reliabilities discussed in previous chapters). The book concludes in chapter 8 with an examination of applications of reliability within engineering and medical fields. Presenting a highly relevant competency for graduates entering product research and development, or facilities operations sectors, this text includes many examples and end of chapter study questions to maximize student comprehension. Explains concepts of reliability and risk estimation techniques in the context of medicine and engineering; Elucidates the interplay between reliability and risk from design to operation phases; Uses real world examples from engineering structures and medical devices and protocols; Adopts a lucid yet rigorous presentation of reliability and risk calculations; Reinforces students understanding of concepts covered with end-of-chapter exercises.
Publisher: Springer Nature
ISBN: 3030804542
Category : Technology & Engineering
Languages : en
Pages : 138
Book Description
This graduate textbook imparts the fundamentals of reliability and risk that can be connected mathematically and applied to problems in engineering and medical science and practice. The book is divided into eight chapters, the first three of which deal with basic fundamentals of probability theory and reliability methods. The fourth chapter illustrates simulation methods needed to solve complex problems. Chapters 5-7 explain reliability codes and system reliability (which uses the component reliabilities discussed in previous chapters). The book concludes in chapter 8 with an examination of applications of reliability within engineering and medical fields. Presenting a highly relevant competency for graduates entering product research and development, or facilities operations sectors, this text includes many examples and end of chapter study questions to maximize student comprehension. Explains concepts of reliability and risk estimation techniques in the context of medicine and engineering; Elucidates the interplay between reliability and risk from design to operation phases; Uses real world examples from engineering structures and medical devices and protocols; Adopts a lucid yet rigorous presentation of reliability and risk calculations; Reinforces students understanding of concepts covered with end-of-chapter exercises.
Cloud Reliability Engineering
Author: Rathnakar Achary
Publisher: CRC Press
ISBN: 1000352072
Category : Business & Economics
Languages : en
Pages : 353
Book Description
Coud reliability engineering is a leading issue of cloud services. Cloud service providers guarantee computation, storage and applications through service-level agreements (SLAs) for promised levels of performance and uptime. Cloud Reliability Engineering: Technologies and Tools presents case studies examining cloud services, their challenges, and the reliability mechanisms used by cloud service providers. These case studies provide readers with techniques to harness cloud reliability and availability requirements in their own endeavors. Both conceptual and applied, the book explains reliability theory and the best practices used by cloud service companies to provide high availability. It also examines load balancing, and cloud security. Written by researchers and practitioners, the book’s chapters are a comprehensive study of cloud reliability and availability issues and solutions. Various reliability class distributions and their effects on cloud reliability are discussed. An important aspect of reliability block diagrams is used to categorize poor reliability of cloud infrastructures, where enhancement can be made to lower the failure rate of the system. This technique can be used in design and functional stages to determine poor reliability of a system and provide target improvements. Load balancing for reliability is examined as a migrating process or performed by using virtual machines. The approach employed to identify the lightly loaded destination node to which the processes/virtual machines migrate can be optimized by employing a genetic algorithm. To analyze security risk and reliability, a novel technique for minimizing the number of keys and the security system is presented. The book also provides an overview of testing methods for the cloud, and a case study discusses testing reliability, installability, and security. A comprehensive volume, Cloud Reliability Engineering: Technologies and Tools combines research, theory, and best practices used to engineer reliable cloud availability and performance.
Publisher: CRC Press
ISBN: 1000352072
Category : Business & Economics
Languages : en
Pages : 353
Book Description
Coud reliability engineering is a leading issue of cloud services. Cloud service providers guarantee computation, storage and applications through service-level agreements (SLAs) for promised levels of performance and uptime. Cloud Reliability Engineering: Technologies and Tools presents case studies examining cloud services, their challenges, and the reliability mechanisms used by cloud service providers. These case studies provide readers with techniques to harness cloud reliability and availability requirements in their own endeavors. Both conceptual and applied, the book explains reliability theory and the best practices used by cloud service companies to provide high availability. It also examines load balancing, and cloud security. Written by researchers and practitioners, the book’s chapters are a comprehensive study of cloud reliability and availability issues and solutions. Various reliability class distributions and their effects on cloud reliability are discussed. An important aspect of reliability block diagrams is used to categorize poor reliability of cloud infrastructures, where enhancement can be made to lower the failure rate of the system. This technique can be used in design and functional stages to determine poor reliability of a system and provide target improvements. Load balancing for reliability is examined as a migrating process or performed by using virtual machines. The approach employed to identify the lightly loaded destination node to which the processes/virtual machines migrate can be optimized by employing a genetic algorithm. To analyze security risk and reliability, a novel technique for minimizing the number of keys and the security system is presented. The book also provides an overview of testing methods for the cloud, and a case study discusses testing reliability, installability, and security. A comprehensive volume, Cloud Reliability Engineering: Technologies and Tools combines research, theory, and best practices used to engineer reliable cloud availability and performance.
Reliability and Statistical Computing
Author: Hoang Pham
Publisher: Springer Nature
ISBN: 3030434125
Category : Technology & Engineering
Languages : en
Pages : 325
Book Description
This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.
Publisher: Springer Nature
ISBN: 3030434125
Category : Technology & Engineering
Languages : en
Pages : 325
Book Description
This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.
Computational Intelligence in Reliability Engineering
Author:
Publisher:
ISBN:
Category : Computational intelligence
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category : Computational intelligence
Languages : en
Pages :
Book Description