Introduction to Fuzzy Reliability

Introduction to Fuzzy Reliability treats fuzzy methodology in hardware reliability and software reliability in a relatively systematic manner. The contents of this book are organized as follows.

Author: Kai-Yuan Cai

Publisher: Springer Science & Business Media

ISBN: 9781461314035

Category: Mathematics

Page: 311

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Introduction to Fuzzy Reliability treats fuzzy methodology in hardware reliability and software reliability in a relatively systematic manner. The contents of this book are organized as follows. Chapter 1 places reliability engineering in the scope of a broader area, i.e. system failure engineering. Readers will find that although this book is confined to hardware and software reliability, it may be useful for other aspects of system failure engineering, like maintenance and quality control. Chapter 2 contains the elementary knowledge of fuzzy sets and possibility spaces which are required reading for the rest of this book. This chapter is included for the overall completeness of the book, but a few points (e.g. definition of conditional possibility and existence theorem of possibility space) may be new. Chapter 3 discusses how to calculate probist system reliability when the component reliabilities are represented by fuzzy numbers, and how to analyze fault trees when probabilities of basic events are fuzzy. Chapter 4 presents the basic theory of profust reliability, whereas Chapter 5 analyzes the profust reliability behavior of a number of engineering systems. Chapters 6 and 7 are devoted to probist reliability theory from two different perspectives. Chapter 8 discusses how to model software reliability behavior by using fuzzy methodology. Chapter 9 includes a number of mathematical problems which are raised by applications of fuzzy methodology in hardware and software reliability, but may be important for fuzzy set and possibility theories.

Introduction to Fuzzy Reliability

Introduction to Fuzzy Reliability treats fuzzy methodology in hardware reliability and software reliability in a relatively systematic manner. The contents of this book are organized as follows.

Author: Kai-Yuan Cai

Publisher: Springer

ISBN: 0792397371

Category: Mathematics

Page: 311

View: 635

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Introduction to Fuzzy Reliability treats fuzzy methodology in hardware reliability and software reliability in a relatively systematic manner. The contents of this book are organized as follows. Chapter 1 places reliability engineering in the scope of a broader area, i.e. system failure engineering. Readers will find that although this book is confined to hardware and software reliability, it may be useful for other aspects of system failure engineering, like maintenance and quality control. Chapter 2 contains the elementary knowledge of fuzzy sets and possibility spaces which are required reading for the rest of this book. This chapter is included for the overall completeness of the book, but a few points (e.g. definition of conditional possibility and existence theorem of possibility space) may be new. Chapter 3 discusses how to calculate probist system reliability when the component reliabilities are represented by fuzzy numbers, and how to analyze fault trees when probabilities of basic events are fuzzy. Chapter 4 presents the basic theory of profust reliability, whereas Chapter 5 analyzes the profust reliability behavior of a number of engineering systems. Chapters 6 and 7 are devoted to probist reliability theory from two different perspectives. Chapter 8 discusses how to model software reliability behavior by using fuzzy methodology. Chapter 9 includes a number of mathematical problems which are raised by applications of fuzzy methodology in hardware and software reliability, but may be important for fuzzy set and possibility theories.

Advancements in Fuzzy Reliability Theory

Fuzzy Sets and Systems, 83(2), 113–133. doi:10.1016/0165-0114(95)00385- 1 Cai, K. Y. (1996). Introduction on Fuzzy Reliability.

Author: Kumar, Akshay

Publisher: IGI Global

ISBN: 9781799875666

Category: Mathematics

Page: 322

View: 878

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In recent years, substantial efforts are being made in the development of reliability theory including fuzzy reliability theories and their applications to various real-life problems. Fuzzy set theory is widely used in decision making and multi criteria such as management and engineering, as well as other important domains in order to evaluate the uncertainty of real-life systems. Fuzzy reliability has proven to have effective tools and techniques based on real set theory for proposed models within various engineering fields, and current research focuses on these applications. Advancements in Fuzzy Reliability Theory introduces the concept of reliability fuzzy set theory including various methods, techniques, and algorithms. The chapters present the latest findings and research in fuzzy reliability theory applications in engineering areas. While examining the implementation of fuzzy reliability theory among various industries such as mining, construction, automobile, engineering, and more, this book is ideal for engineers, practitioners, researchers, academicians, and students interested in fuzzy reliability theory applications in engineering areas.

Computational Intelligence in Reliability Engineering

Cai K Y. System failure engineering and fuzzy methodology: An introductory overview. Fuzzy Sets and Systems, 1996, 83: 113-133 Cooman G de.

Author: Gregory Levitin

Publisher: Springer Science & Business Media

ISBN: 9783540373711

Category: Mathematics

Page: 413

View: 943

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This volume includes chapters presenting applications of different metaheuristics in reliability engineering, including ant colony optimization, great deluge algorithm, cross-entropy method and particle swarm optimization. It also presents chapters devoted to cellular automata and support vector machines, and applications of artificial neural networks, a powerful adaptive technique that can be used for learning, prediction and optimization. Several chapters describe aspects of imprecise reliability and applications of fuzzy and vague set theory.

Multi state System Reliability Analysis and Optimization for Engineers and Industrial Managers

Cai K (1996) Introduction to fuzzy reliability. Kluwer, Amsterdam Chen SM (1994) Fuzzy system reliability analysis using fuzzy number arithmetic operations.

Author: Anatoly Lisnianski

Publisher: Springer Science & Business Media

ISBN: 1849963207

Category: Technology & Engineering

Page: 393

View: 974

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Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers 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, but is also practically oriented. New theoretical issues are described, including: • combined Markov and semi-Markov processes methods, and universal generating function techniques; • statistical data processing for MSSs; • reliability analysis of aging MSSs; • methods for cost-reliability and cost-availability analysis of MSSs; and • main definitions and concepts of fuzzy MSS. Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers also discusses life cycle cost analysis and practical optimal decision making for real world MSSs. Numerous examples are included in each section in order to illustrate mathematical tools. Besides these examples, real world MSSs (such as power generating and transmission systems, air-conditioning systems, production systems, etc.) are considered as case studies. Multi-state System Reliability Analysis and Optimization for Engineers and Industrial Managers also describes basic concepts of MSS, MSS reliability measures and tools for MSS reliability assessment and optimization. It is a self-contained study resource and does not require prior knowledge from its readers, making the book attractive for researchers as well as for practical engineers and industrial managers.

Performance Prediction and Analytics of Fuzzy Reliability and Queuing Models

... problem solution · Trapezoidal 1 Introduction Fuzzy set theory has been extensively used in the area where the information/data is vague or imprecise.

Author: Kusum Deep

Publisher: Springer

ISBN: 9789811308574

Category: Business & Economics

Page: 282

View: 307

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This book presents the latest developments and breakthroughs in fuzzy theory and performance prediction of queuing and reliability models by using the stochastic modeling and optimization theory. The main focus is on analytics that use fuzzy logic, queuing and reliability theory for the performance prediction and optimal design of real-time engineering systems including call centers, telecommunication, manufacturing, service organizations, etc. For the day-to-day as well as industrial queuing situations and reliability prediction of machining parts embedded in computer, communication and manufacturing systems, the book assesses various measures of performance and effectiveness that can provide valuable insights and help arrive at the best decisions with regard to service and engineering systems. In twenty chapters, the book presents both theoretical developments and applications of the fuzzy logic, reliability and queuing models in a diverse range of scenarios. The topics discussed will be of interest to researchers, educators and undergraduate students in the fields of Engineering, Business Management, and the Mathematical Sciences.

Safety Reliability and Risk Analysis

Introduction to Fuzzy Reliability. Boston: Kluwer. Coolen, F.P.A. 2004. On the use of imprecise probabilities in reliability. Quality and Reliability ...

Author: Sebastian Martorell

Publisher: CRC Press

ISBN: 9781482266481

Category: Technology & Engineering

Page: 3510

View: 356

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Safety, Reliability and Risk Analysis. Theory, Methods and Applications contains the papers presented at the joint ESREL (European Safety and Reliability) and SRA-Europe (Society for Risk Analysis Europe) Conference (Valencia, Spain, 22-25 September 2008). The book covers a wide range of topics, including: Accident and Incident Investigation; Crisi

Advances in System Reliability Engineering

[11] K.-Y. Cay, Introduction to Fuzzy Reliability, Kluwer Academic Publishers, Dordrecht, 1996. [12] A. Rotshtein, Fuzzy reliability analysis of man-machine ...

Author: Mangey Ram

Publisher: Academic Press

ISBN: 9780128162729

Category: Technology & Engineering

Page: 318

View: 906

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Recent Advances in System Reliability Engineering describes and evaluates the latest tools, techniques, strategies, and methods in this topic for a variety of applications. Special emphasis is put on simulation and modelling technology which is growing in influence in industry, and presents challenges as well as opportunities to reliability and systems engineers. Several manufacturing engineering applications are addressed, making this a particularly valuable reference for readers in that sector. Contains comprehensive discussions on state-of-the-art tools, techniques, and strategies from industry Connects the latest academic research to applications in industry including system reliability, safety assessment, and preventive maintenance Gives an in-depth analysis of the benefits and applications of modelling and simulation to reliability

Reliability Calculations with the Stochastic Finite Element

Fuzzy Optimization Method for Series System CONCLUDING REMARKS CONSENT FOR PUBLICATION CONFLICT OF INTEREST ACKNOWLEDGEMENTS REFERENCES .

Author: Wenhui Mo

Publisher: Bentham Science Publishers

ISBN: 9789811485510

Category: Science

Page: 117

View: 350

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Reliability Calculations with the Stochastic Finite Element presents different methods of reliability analysis for systems. Chapters explain methods used to analyze a number of systems such as single component maintenance system, repairable series system, rigid rotor balance, spring mechanics, gearbox design and optimization, and nonlinear vibration. The author proposes several established and new methods to solve reliability problems which are based on fuzzy systems, sensitivity analysis, Monte Carlo simulation, HL-RF methods, differential equations, and stochastic finite element processing, to name a few. This handbook is a useful update on reliability analysis for mechanical engineers and technical apprentices.

Fuzzy Evidence in Identification Forecasting and Diagnosis

Cai, K.-Y.: Introduction to Fuzzy Reliability, p. 290. Kluwer Academic Publishers, New York (1996) 42. Rotshtein, A.: Fuzzy Reliability Analysis of ...

Author: Alexander P. Rotshtein

Publisher: Springer Science & Business Media

ISBN: 9783642257858

Category: Computers

Page: 313

View: 268

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The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving. The book is organised as follows: Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fuzzy relations and fuzzy rules. Chapter 8 presents a method for extracting fuzzy relations from data. All the algorithms presented in Chapters 2-8 are validated by computer experiments and illustrated by solving medical and technical forecasting and diagnosis problems. Finally, Chapter 9 includes applications of the proposed methodology in dynamic and inventory control systems, prediction of results of football games, decision making in road accident investigations, project management and reliability analysis.

Uncertainty Modeling and Analysis in Civil Engineering

Cai , K.-Y. , Introduction to Fuzzy Reliability , Kluwer Academic Publishers , 1996 . 12. Duckstein , L. , and Parent , E. , Systems engineering of natural ...

Author: Bilal M. Ayyub

Publisher: CRC Press

ISBN: 0849331080

Category: Technology & Engineering

Page: 528

View: 293

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With the expansion of new technologies, materials, and the design of complex systems, the expectations of society upon engineers are becoming larger than ever. Engineers make critical decisions with potentially high adverse consequences. The current political, societal, and financial climate requires engineers to formally consider the factors of uncertainty (e.g., floods, earthquakes, winds, environmental risks) in their decisions at all levels. Uncertainty Modeling and Analysis in Civil Engineering provides a thorough report on the immediate state of uncertainty modeling and analytical methods for civil engineering systems, presenting a toolbox for solving problems in real-world situations. Topics include Neural networks Genetic algorithms Numerical modeling Fuzzy sets and operations Reliability and risk analysis Systems control Uncertainty in probability estimates This compendium is a considerable reference for civil engineers as well as for engineers in other disciplines, computer scientists, general scientists, and students.

Fuzzy Logic and Mathematics

Introduction to Fuzzy Reliability. Dordrecht: Kluwer. Cai, K. Y., C. Y. Wen, and M. L. Zhang. 1991a. Fuzzy reliability modeling of gracefully degradable ...

Author: Radim Belohlavek

Publisher: Oxford University Press

ISBN: 9780190200022

Category: Philosophy

Page: 480

View: 418

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The term "fuzzy logic," as it is understood in this book, stands for all aspects of representing and manipulating knowledge based on the rejection of the most fundamental principle of classical logic---the principle of bivalence. According to this principle, each declarative sentence is required to be either true or false. In fuzzy logic, these classical truth values are not abandoned. However, additional, intermediate truth values between true and false are allowed, which are interpreted as degrees of truth. This opens a new way of thinking---thinking in terms of degrees rather than absolutes. For example, it leads to the definition of a new kind of sets, referred to as fuzzy sets, in which membership is a matter of degree. The book examines the genesis and development of fuzzy logic. It surveys the prehistory of fuzzy logic and inspects circumstances that eventually lead to the emergence of fuzzy logic. The book explores in detail the development of propositional, predicate, and other calculi that admit degrees of truth, which are known as fuzzy logic in the narrow sense. Fuzzy logic in the broad sense, whose primary aim is to utilize degrees of truth for emulating common-sense human reasoning in natural language, is scrutinized as well. The book also examines principles for developing mathematics based on fuzzy logic and provides overviews of areas in which this has been done most effectively. It also presents a detailed survey of established and prospective applications of fuzzy logic in various areas of human affairs, and provides an assessment of the significance of fuzzy logic as a new paradigm.

Belief Reliability Theory and Methodology

Blockley and Hoffman are the earliest scholars to introduce fuzzy theory into the research of reliability and safety. Blockley proposes that in structural ...

Author: Rui Kang

Publisher: Springer Nature

ISBN: 9789811608230

Category: Technology & Engineering

Page: 187

View: 878

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This book, from the perspective of reliability science construction, proposes a new theory called BELIEF RELIABILITY theory on the basis of probability theory, uncertainty theory and chance theory. The main topics include the philosophical basis of reliability science, the principles of reliability science, the criteria of reasonable reliability metrics and the basic theoretical framework and methodology of belief reliability theory. In this book, the belief reliability metric, analysis, design and evaluation methods will provide readers with a brand-new perspective on reliability applications and uncertainty quantification.

Advanced Signal Processing Technology by Soft Computing

[3] K.Y. Cai, "Introduction to fuzzy reliability”, Kluwer Academic Publishers, 1996. [4] F.P.A. Coolen, M.J. Newby, "Bayesian reliability analysis with ...

Author: Charles Hsu

Publisher: World Scientific

ISBN: 9789814492126

Category: Computers

Page: 308

View: 945

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This book presents worldwide outstanding research and recent progress in the applications of neural networks, fuzzy logic, chaos, independent component analysis, etc to fields related to speech recognition enhancement, supervised Fourier demixing noise elimination, acoustic databases, the human hearing system, cancer detection, image processing, and visual communications. Contents:Speech Hyphenation Segmentation by Means of Blind Source Separation (H Szu & C Hsu)Higher-Order Moments Based Synthesis of Supervised Fourier Demixing Filter (E Uchino et al.)Design and Application of an Acoustic Database Navigator for the Interactive Analysis of Psychoacoustic Sound Archives and Sound Engineering (A Konig et al.)Multilayer Perception Networks with Adaptive Centroid Transformation (M Lehtokangas)Identification and Analysis for Transiently Evoked Otoacoustic Emission (L-M Li et al.)New Reliability Models Based on Imprecise Probabilities (L V Utkin & S V Gurov)Multi-Modular Neural Network for Breast Cancer Detection (H Li & K J R Liu)Advanced Neural Nets for Visual Image Communication (H Szu & C Hsu)Continuous Valued Techniques Based on the Lagrangian Method for the Wire Routing Problem (S Ismail et al.)Chaotic Neural Networks for Information Processing (C Hsu & H Szu)Wavelet Encoding for Interactive Genetic Algorithm in Emotional Image Retrieval (J-Y Lee & S-B Cho)A Call Admission Control Using Interval Arithmetic Coulomb Energy Network (W D Lee et al.) Readership: Upper level undergraduates, graduate students, researchers, academic lecturers and senior engineers in fuzzy logic, machine perception and pattern recognition. Keywords:Neural Networks;Artificial Intelligence;Fuzzy Logic;Soft Computing;Chaos;Speech Signal Processing;Independent Component Analysis;Information Processing;Hebbain Learning;Nonlinear Dynamics;Adaptive Wavelet Transforms;Blind Source Separation;Genetic Algorithm;Emotional Information Processing;Statistical Analysis;Principle Component Analysis;Multilayer Perception Networks

Safety Reliability Risk and Life Cycle Performance of Structures and Infrastructures

First, a short introduction to fuzzy arithmetic will be given, followed by the description of the sparse-grid methodology used for the surrogate-model ...

Author: George Deodatis

Publisher: CRC Press

ISBN: 9781315884882

Category: Technology & Engineering

Page: 1112

View: 203

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Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures contains the plenary lectures and papers presented at the 11th International Conference on STRUCTURAL SAFETY AND RELIABILITY (ICOSSAR2013, New York, NY, USA, 16-20 June 2013), and covers major aspects of safety, reliability, risk and life-cycle performance of str

Fuzzy Neural Network Theory and Application

[ 7 ] Cai K. Y. , Introduction to Fuzzy Reliability , Boston Dordrecht London : Kluwer Academic Publishers , 1996 . [ 8 ] Carpenter G. A. & Grossberg S.

Author: Puyin Liu

Publisher: World Scientific

ISBN: 9812794212

Category: Computers

Page: 376

View: 540

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This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to help the reader grasp the underlying theory. This is a valuable reference for scientists and engineers working in mathematics, computer science, control or other fields related to information processing. It can also be used as a textbook for graduate courses in applied mathematics, computer science, automatic control and electrical engineering. Contents: Fuzzy Neural Networks for Storing and Classifying; Fuzzy Associative Memory OCo Feedback Networks; Regular Fuzzy Neural Networks; Polygonal Fuzzy Neural Networks; Approximation Analysis of Fuzzy Systems; Stochastic Fuzzy Systems and Approximations; Application of FNN to Image Restoration. Readership: Scientists, engineers and graduate students in applied mathematics, computer science, automatic control and information processing."