A Sampling Based Computational Strategy For The Representation Of Epistemic Uncertainty In Model Predictions With Evidence Theory
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A Sampling Based Computational Strategy For The Representation Of Epistemic Uncertainty In Model Predictions With Evidence Theory
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Author : Jon C. Helton
language : en
Publisher:
Release Date : 2006
A Sampling Based Computational Strategy For The Representation Of Epistemic Uncertainty In Model Predictions With Evidence Theory written by Jon C. Helton and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Dempster-Shafer theory categories.
A Sampling Based Computational Strategy For The Representation Of Epistemic Uncertainty In Model Predictions With Evidence Theory
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Author : J. D. Johnson
language : en
Publisher:
Release Date : 2006
A Sampling Based Computational Strategy For The Representation Of Epistemic Uncertainty In Model Predictions With Evidence Theory written by J. D. Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a model is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.
Uncertainty In Industrial Practice
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Author : Etienne de Rocquigny
language : en
Publisher: John Wiley & Sons
Release Date : 2008-09-15
Uncertainty In Industrial Practice written by Etienne de Rocquigny and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-15 with Mathematics categories.
Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control. Authored by a leading European network of experts representing a cross section of industries, Uncertainty in Industrial Practice aims to provide a reference for the dissemination of uncertainty treatment in any type of industry. It is concerned with the quantification of uncertainties in the presence of data, model(s) and knowledge about the system, and offers a technical contribution to decision-making processes whilst acknowledging industrial constraints. The approach presented can be applied to a range of different business contexts, from research or early design through to certification or in-service processes. The authors aim to foster optimal trade-offs between literature-referenced methodologies and the simplified approaches often inevitable in practice, owing to data, time or budget limitations of technical decision-makers. Uncertainty in Industrial Practice: Features recent uncertainty case studies carried out in the nuclear, air & space, oil, mechanical and civil engineering industries set in a common methodological framework. Presents methods for organizing and treating uncertainties in a generic and prioritized perspective. Illustrates practical difficulties and solutions encountered according to the level of complexity, information available and regulatory and financial constraints. Discusses best practice in uncertainty modeling, propagation and sensitivity analysis through a variety of statistical and numerical methods. Reviews recent standards, references and available software, providing an essential resource for engineers and risk analysts in a wide variety of industries. This book provides a guide to dealing with quantitative uncertainty in engineering and modelling and is aimed at practitioners, including risk-industry regulators and academics wishing to develop industry-realistic methodologies.
Advanced Engineering And Technology
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Author : Liquan Xie
language : en
Publisher: CRC Press
Release Date : 2014-03-18
Advanced Engineering And Technology written by Liquan Xie and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-18 with Technology & Engineering categories.
Advanced Engineering and Technology contains 110 technical papers from the 2014 Annual Congress on Advanced Engineering and Technology (CAET 2014, Hong Kong, 19-20 April 2014, including the 4th Workshop on Applied Mechanics and Civil Engineering, AMCE 2014). The contributions focus on advanced theories and technologies related to building engineering, geotechnical engineering, road and bridge engineering, hydraulic engineering, environmental engineering, pollution and control, water resources and water treatment, mechanics in engineering, water and soil conservation, numerical software and applications, climate change and environmental dynamics, intelligent safety systems, chemistry, biochemical and food engineering, and modelling and data analysis. Advanced Engineering and Technology will be useful to academics and professionals involved in civil engineering, hydraulic engineering, environmental engineering, modelling & data analysis, chemistry and biochemical engineering, and other related fields.
Aerospace System Analysis And Optimization In Uncertainty
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Author : Loïc Brevault
language : en
Publisher: Springer Nature
Release Date : 2020-08-26
Aerospace System Analysis And Optimization In Uncertainty written by Loïc Brevault and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-26 with Mathematics categories.
Spotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties. The book provides approaches to integrating a multitude of components and constraints with the ultimate goal of reducing design cycles. Insights on a vast assortment of problems are provided, including discipline modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization. The extensive range of topics covered include areas of current open research. This Work is destined to become a fundamental reference for aerospace systems engineers, researchers, as well as for practitioners and engineers working in areas of optimization and uncertainty. Part I is largely comprised of fundamentals. Part II presents methodologies for single discipline problems with a review of existing uncertainty propagation, reliability analysis, and optimization techniques. Part III is dedicated to the uncertainty-based MDO and related issues. Part IV deals with three MDO related issues: the multifidelity, the multi-objective optimization and the mixed continuous/discrete optimization and Part V is devoted to test cases for aerospace vehicle design.
Optimization Under Uncertainty With Applications To Aerospace Engineering
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Author : Massimiliano Vasile
language : en
Publisher: Springer Nature
Release Date : 2021-02-15
Optimization Under Uncertainty With Applications To Aerospace Engineering written by Massimiliano Vasile and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-15 with Science categories.
In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.
Multidisciplinary Design Optimization And Its Application In Deep Manned Submersible Design
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Author : Binbin Pan
language : en
Publisher: Springer Nature
Release Date : 2020-08-28
Multidisciplinary Design Optimization And Its Application In Deep Manned Submersible Design written by Binbin Pan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-28 with Technology & Engineering categories.
This book investigates Reliability-based Multidisciplinary Design Optimization (RBMDO) theory and its application in the design of deep manned submersibles (DMSs). Multidisciplinary Design Optimization (MDO) is an effective design method for large engineering systems like aircraft, warships, and satellites, which require designers and engineers from various disciplines to cooperate with each other. MDO can be used to handle the conflicts that arise between these disciplines, and focuses on the optimal design of the system as a whole. However, it can also push designs to the brink of failure. In order to keep the system balanced, Reliability-based Design (RBD) must be incorporated into MDO. Consequently, new algorithms and methods have to be developed for RBMDO theory. This book provides an essential overview of MDO, RBD, and RBMDO and subsequently introduces key algorithms and methods by means of case analyses. In closing, it introduces readers to the design of DMSs and applies RBMDO methods to the design of the manned hull and the general concept design. The book is intended for all students and researchers who are interested in system design theory, and for engineers working on large, complex engineering systems.
Sensitivity In Risk Analyses With Uncertain Numbers
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Author : Scott Ferson
language : en
Publisher:
Release Date : 2006
Sensitivity In Risk Analyses With Uncertain Numbers written by Scott Ferson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Dempster-Shafer theory categories.
Generalized Measure Theory
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Author : Zhenyuan Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-07
Generalized Measure Theory written by Zhenyuan Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-07 with Mathematics categories.
Generalized Measure Theory examines the relatively new mathematical area of generalized measure theory. The exposition unfolds systematically, beginning with preliminaries and new concepts, followed by a detailed treatment of important new results regarding various types of nonadditive measures and the associated integration theory. The latter involves several types of integrals: Sugeno integrals, Choquet integrals, pan-integrals, and lower and upper integrals. All of the topics are motivated by numerous examples, culminating in a final chapter on applications of generalized measure theory. Some key features of the book include: many exercises at the end of each chapter along with relevant historical and bibliographical notes, an extensive bibliography, and name and subject indices. The work is suitable for a classroom setting at the graduate level in courses or seminars in applied mathematics, computer science, engineering, and some areas of science. A sound background in mathematical analysis is required. Since the book contains many original results by the authors, it will also appeal to researchers working in the emerging area of generalized measure theory.
Data Uncertainty And Important Measures
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Author : Christophe Simon
language : en
Publisher: John Wiley & Sons
Release Date : 2018-01-19
Data Uncertainty And Important Measures written by Christophe Simon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-19 with Mathematics categories.
The first part of the book defines the concept of uncertainties and the mathematical frameworks that will be used for uncertainty modeling. The application to system reliability assessment illustrates the concept. In the second part, evidential networks as a new tool to model uncertainty in reliability and risk analysis is proposed and described. Then it is applied on SIS performance assessment and in risk analysis of a heat sink. In the third part, Bayesian and evidential networks are used to deal with important measures evaluation in the context of uncertainties.