Solutions Manual for Uncertainty Modeling and Analysis in Engineering and the Sciences PDF Download
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Author: Bilal M. Ayyub
Publisher: Chapman & Hall
ISBN: 9781584886563
Category : Business & Economics
Languages : en
Pages : 110
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Book Description
Author: Bilal M. Ayyub
Publisher: Chapman & Hall
ISBN: 9781584886563
Category : Business & Economics
Languages : en
Pages : 110
Get Book
Book Description
Author: Bilal M. Ayyub
Publisher: Chapman and Hall/CRC
ISBN: 9781584886440
Category : Business & Economics
Languages : en
Pages : 400
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Book Description
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.
Author: Bilal M. Ayyub
Publisher: Springer Science & Business Media
ISBN: 146155473X
Category : Computers
Languages : en
Pages : 376
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Book Description
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.
Author: Bilal Ayyub
Publisher: Springer
ISBN: 9781461554745
Category : Computers
Languages : en
Pages : 371
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Book Description
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.
Author: Faith A. Morrison
Publisher: Cambridge University Press
ISBN: 1108478352
Category : Computers
Languages : en
Pages : 389
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Book Description
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.
Author: Snehashish Chakraverty
Publisher:
ISBN: 9781466649941
Category : Civil engineering
Languages : en
Pages : 0
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Book Description
"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"--
Author: Ryan G. McClarren
Publisher: Springer
ISBN: 3319995251
Category : Science
Languages : en
Pages : 345
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Book Description
This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.
Author: Snehashish Chakraverty
Publisher:
ISBN: 9781466649934
Category : Civil engineering
Languages : en
Pages : 442
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Book Description
Author: Haym Benaroya
Publisher: CRC Press
ISBN: 9780824753801
Category : Technology & Engineering
Languages : en
Pages : 746
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Book Description
An effective text must be well balanced and thorough in its approach to a topic as expansive as vibration, and Mechanical Vibration is just such a textbook. Written for both senior undergraduate and graduate course levels, this updated and expanded second edition integrates uncertainty and control into the discussion of vibration, outlining basic concepts before delving into the mathematical rigors of modeling and analysis. Mechanical Vibration: Analysis, Uncertainties, and Control, Second Edition provides example problems, end-of-chapter exercises, and an up-to-date set of mini-projects to enhance students' computational abilities and includes abundant references for further study or more in-depth information. The author provides a MATLAB® primer on an accompanying CD-ROM, which contains original programs that can be used to solve complex problems and test solutions. The book is self-contained, covering both basic and more advanced topics such as stochastic processes and variational approaches. It concludes with a completely new chapter on nonlinear vibration and stability. Professors will find that the logical sequence of material is ideal for tailoring individualized syllabi, and students will benefit from the abundance of problems and MATLAB programs provided in the text and on the accompanying CD-ROM, respectively. A solutions manual is also available with qualifying course adoptions.
Author: Stuart A. Klugman
Publisher: John Wiley & Sons
ISBN: 1118472020
Category : Business & Economics
Languages : en
Pages : 258
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Book Description
Student Solutions Manual to Accompany Loss Models: From Data to Decisions, Fourth Edition. This volume is organised around the principle that much of actuarial science consists of the construction and analysis of mathematical models which describe the process by which funds flow into and out of an insurance system.
