Uncertainty Modeling and Analysis in Engineering and the Sciences

Uncertainty Modeling and Analysis in Engineering and the Sciences
Author: Bilal M. Ayyub,George J. Klir
Publsiher: Chapman and Hall/CRC
Total Pages: 400
Release: 2006-05-25
Genre: Business & Economics
ISBN: 1584886447

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Engineers and scientists often need to solve complex problems with incomplete information resources, necessitating a proper treatment of uncertainty and a reliance on expert opinions. Uncertainty Modeling and Analysis in Engineering and the Sciences prepares current and future analysts and practitioners to understand the fundamentals of knowledge and ignorance, how to model and analyze uncertainty, and how to select appropriate analytical tools for particular problems. This volume covers primary components of ignorance and their impact on practice and decision making. It provides an overview of the current state of uncertainty modeling and analysis, and reviews emerging theories while emphasizing practical applications in science and engineering. The book introduces fundamental concepts of classical, fuzzy, and rough sets, probability, Bayesian methods, interval analysis, fuzzy arithmetic, interval probabilities, evidence theory, open-world models, sequences, and possibility theory. The authors present these methods to meet the needs of practitioners in many fields, emphasizing the practical use, limitations, advantages, and disadvantages of the methods.

Solutions Manual for Uncertainty Modeling and Analysis in Engineering and the Sciences

Solutions Manual for Uncertainty Modeling and Analysis in Engineering and the Sciences
Author: Bilal M. Ayyub,George J. Klir
Publsiher: Chapman & Hall
Total Pages: 110
Release: 2006-01
Genre: Business & Economics
ISBN: 1584886560

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Uncertainty Analysis in Engineering and Sciences Fuzzy Logic Statistics and Neural Network Approach

Uncertainty Analysis in Engineering and Sciences  Fuzzy Logic  Statistics  and Neural Network Approach
Author: Bilal M. Ayyub,Madan M. Gupta
Publsiher: Springer Science & Business Media
Total Pages: 376
Release: 2012-12-06
Genre: Computers
ISBN: 9781461554738

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Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.

Uncertainty Analysis in Engineering and Sciences Fuzzy Logic Statistics and Neural Network Approach

Uncertainty Analysis in Engineering and Sciences  Fuzzy Logic  Statistics  and Neural Network Approach
Author: Bilal Ayyub,Madan M. Gupta
Publsiher: Springer
Total Pages: 371
Release: 2011-09-28
Genre: Computers
ISBN: 1461554748

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Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.

Applied Research in Uncertainty Modeling and Analysis

Applied Research in Uncertainty Modeling and Analysis
Author: Bilal M. Ayyub
Publsiher: Springer Science & Business Media
Total Pages: 547
Release: 2007-12-29
Genre: Business & Economics
ISBN: 9780387235509

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The application areas of uncertainty are numerous and diverse, including all fields of engineering, computer science, systems control and finance. Determining appropriate ways and methods of dealing with uncertainty has been a constant challenge. The theme for this book is better understanding and the application of uncertainty theories. This book, with invited chapters, deals with the uncertainty phenomena in diverse fields. The book is an outgrowth of the Fourth International Symposium on Uncertainty Modeling and Analysis (ISUMA), which was held at the center of Adult Education, College Park, Maryland, in September 2003. All of the chapters have been carefully edited, following a review process in which the editorial committee scrutinized each chapter. The contents of the book are reported in twenty-three chapters, covering more than . . ... pages. This book is divided into six main sections. Part I (Chapters 1-4) presents the philosophical and theoretical foundation of uncertainty, new computational directions in neural networks, and some theoretical foundation of fuzzy systems. Part I1 (Chapters 5-8) reports on biomedical and chemical engineering applications. The sections looks at noise reduction techniques using hidden Markov models, evaluation of biomedical signals using neural networks, and changes in medical image detection using Markov Random Field and Mean Field theory. One of the chapters reports on optimization in chemical engineering processes.

Uncertainty Modeling and Analysis in Engineering and the Sciences

Uncertainty Modeling and Analysis in Engineering and the Sciences
Author: Bilal M. Ayyub,George J. Klir
Publsiher: CRC Press
Total Pages: 401
Release: 2006-05-25
Genre: Business & Economics
ISBN: 9781420011456

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Engineers and scientists often need to solve complex problems with incomplete information resources, necessitating a proper treatment of uncertainty and a reliance on expert opinions. Uncertainty Modeling and Analysis in Engineering and the Sciences prepares current and future analysts and practitioners to understand the fundamentals of knowledge a

Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems

Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems
Author: Chakraverty, S.
Publsiher: IGI Global
Total Pages: 442
Release: 2014-01-31
Genre: Mathematics
ISBN: 9781466649927

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"This book provides the reader with basic concepts for soft computing and other methods for various means of uncertainty in handling solutions, analysis, and applications"--Provided by publisher.

Uncertainty Analysis for Engineers and Scientists

Uncertainty Analysis for Engineers and Scientists
Author: Faith A. Morrison
Publsiher: Cambridge University Press
Total Pages: 389
Release: 2021-01-07
Genre: Computers
ISBN: 9781108478359

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Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various steps. Provides a systematic, worksheet-based process to determine error limits on measured quantities, and all likely sources of uncertainty are explored, measured or estimated. Features instructions on how to carry out error analysis using Excel and MATLAB®, making previously tedious calculations easy. Whether you are new to the sciences or an experienced engineer, this useful resource provides a practical approach to performing error analysis. Suitable as a text for a junior or senior level laboratory course in aerospace, chemical and mechanical engineering, and for professionals.