Reliability Engineering and Computational Intelligence

Reliability Engineering and Computational Intelligence PDF Author: Coen van Gulijk
Publisher: Springer Nature
ISBN: 3030745562
Category : Technology & Engineering
Languages : en
Pages : 307

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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

Reliability Engineering and Computational Intelligence PDF Author: Coen van Gulijk
Publisher: Springer Nature
ISBN: 3030745562
Category : Technology & Engineering
Languages : en
Pages : 307

Get Book Here

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.

Computational Intelligence in Design and Manufacturing

Computational Intelligence in Design and Manufacturing PDF Author: Andrew Kusiak
Publisher: John Wiley & Sons
ISBN: 9780471348795
Category : Technology & Engineering
Languages : en
Pages : 562

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Book Description
Von der Produktidee über den Prototyp und die Modellsimulation bis zur Analyse: Dieser Band hilft Entwicklern und Designern beim Verständnis aller Abläufe im Zuge des Designs neuer Produkte, Prozesse und Systeme. Eine Fülle von Beispielen industrieller Anwendungen, realer Probleme und zugehöriger Lösungen hilft beim Vertiefen und Umsetzen des Stoffes. (05/00)

Computational Intelligence in Power Engineering

Computational Intelligence in Power Engineering PDF Author: Ajith Abraham
Publisher: Springer
ISBN: 3642140130
Category : Technology & Engineering
Languages : en
Pages : 385

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Book Description
Computational Intelligence (CI) is one of the most important powerful tools for research in the diverse fields of engineering sciences ranging from traditional fields of civil, mechanical engineering to vast sections of electrical, electronics and computer engineering and above all the biological and pharmaceutical sciences. The existing field has its origin in the functioning of the human brain in processing information, recognizing pattern, learning from observations and experiments, storing and retrieving information from memory, etc. In particular, the power industry being on the verge of epoch changing due to deregulation, the power engineers require Computational intelligence tools for proper planning, operation and control of the power system. Most of the CI tools are suitably formulated as some sort of optimization or decision making problems. These CI techniques provide the power utilities with innovative solutions for efficient analysis, optimal operation and control and intelligent decision making. This edited volume deals with different CI techniques for solving real world Power Industry problems. The technical contents will be extremely helpful for the researchers as well as the practicing engineers in the power industry.

New Computational Methods in Power System Reliability

New Computational Methods in Power System Reliability PDF Author: David Elmakias
Publisher: Springer Science & Business Media
ISBN: 3540778101
Category : Mathematics
Languages : en
Pages : 416

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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 Techniques and Their Applications to Software Engineering Problems

Computational Intelligence Techniques and Their Applications to Software Engineering Problems PDF Author: Ankita Bansal
Publisher: CRC Press
ISBN: 1000191923
Category : Computers
Languages : en
Pages : 267

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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 Reliability Engineering

Computational Intelligence in Reliability Engineering PDF Author:
Publisher:
ISBN:
Category : Computational intelligence
Languages : en
Pages :

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Book Description


Computational Intelligence in Time Series Forecasting

Computational Intelligence in Time Series Forecasting PDF Author: Ajoy K. Palit
Publisher: Springer Science & Business Media
ISBN: 1846281849
Category : Computers
Languages : en
Pages : 382

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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 in Software Engineering

Computational Intelligence in Software Engineering PDF Author: Witold Pedrycz
Publisher: World Scientific
ISBN: 9789810235031
Category : Computers
Languages : en
Pages : 504

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Book Description
This unique volume is the first publication on software engineering and computational intelligence (CI) viewed as a synergistic interplay of neurocomputing, granular computation (including fuzzy sets and rough sets), and evolutionary methods. It presents a unified view of CI in the context of software engineering. The book addresses a number of crucial issues: what is CI, what role does it play in software development, how are CI elements built into successive phases of the software life cycle, and what is the role played by CI in quantifying fundamental features of software artifacts? With contributions from leading researchers and practitioners, the book provides the reader with a wealth of new concepts and approaches, complete algorithms, in-depth case studies, and thought-provoking exercises. The topics coverage include neurocomputing, granular as well as evolutionary computing, object-oriented analysis and design in software engineering. There is also an extensive bibliography.

Intelligent Engineering Systems and Computational Cybernetics

Intelligent Engineering Systems and Computational Cybernetics PDF Author: J.A. Tenreiro Machado
Publisher: Springer Science & Business Media
ISBN: 1402086784
Category : Computers
Languages : en
Pages : 438

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Book Description
Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling. The conventional analytical techniques-based approaches for describing and predicting the behaviour of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model. These approaches normally are too categorical in the sense that in the name of “modelling accuracy” they try to describe all the structural details of the real physical system to be modelled. This can significantly increase the intricacy of the model and may result in a enormous computational burden without achieving considerable improvement of the solution. The best paradigm exemplifying this situation may be the classic perturbation theory: the less significant the achievable correction, the more work has to be invested to obtain it. A further important component of machine intelligence is a kind of “structural uniformity” giving room and possibility to model arbitrary particular details a priori not specified and unknown. This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This “learning ability” is a key element of machine intelligence. The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing, evolutionary computation and probabilistic reasoning are of complementary nature and that the best results can be applied by their combined application. Today, the two complementary branches of Machine Intelligence, that is, Artificial Intelligence and Computational Intelligence serve as the basis of Intelligent Engineering Systems. The huge number of scientific results published in Journal and conference proceedings worldwide substantiates this statement. The present book contains several articles taking different viewpoints in the field of intelligent systems.

Reliability and Statistical Computing

Reliability and Statistical Computing PDF Author: Hoang Pham
Publisher: Springer Nature
ISBN: 3030434125
Category : Technology & Engineering
Languages : en
Pages : 325

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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.