Ignorance and Uncertainty, Compte Olivier, Postlewaite Andrew

Автор: Sullivan, T.J.
Название: Introduction to Uncertainty Quantification
ISBN: 3319233947 ISBN-13(EAN): 9783319233949
Издательство: Springer
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Цена: 55890.00 T
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Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favorite problems to understand their strengths and weaknesses, also making the text suitable for a self-study. Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation and numerous application areas in science and engineering. This text is designed as an introduction to UQ for senior undergraduate and graduate students with a mathematical or statistical background and also for researchers from the mathematical sciences or from applications areas who are interested in the field.

Автор: Harald Held
Название: Shape Optimization under Uncertainty from a Stochastic Programming Point of View
ISBN: 3834809098 ISBN-13(EAN): 9783834809094
Издательство: Springer
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Цена: 97820.00 T
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Описание: Optimization problems whose constraints involve partial differential equations (PDEs) are relevant in many areas of technical, industrial, and economic app- cations. At the same time, they pose challenging mathematical research problems in numerical analysis and optimization. The present text is among the ?rst in the research literature addressing stochastic uncertainty in the context of PDE constrained optimization. The focus is on shape optimization for elastic bodies under stochastic loading. Analogies to ?nite dim- sional two-stage stochastic programming drive the treatment, with shapes taking the role of nonanticipative decisions.The main results concern level set-based s- chastic shape optimization with gradient methods involving shape and topological derivatives. The special structure of the elasticity PDE enables the numerical - lution of stochastic shape optimization problems with an arbitrary number of s- narios without increasing the computational effort signi?cantly. Both risk neutral and risk averse models are investigated. This monograph is based on a doctoral dissertation prepared during 2004-2008 at the Chair of Discrete Mathematics and Optimization in the Department of Ma- ematics of the University of Duisburg-Essen. The work was supported by the Deutsche Forschungsgemeinschaft (DFG) within the Priority Program "Optimi- tion with Partial Differential Equations." Rudiger Schultz Acknowledgments I owe a great deal to my supervisors, colleagues, and friends who have always supported, encouraged, andenlightenedmethroughtheirownresearch, comments, and questions.

Автор: Herbert I. Weisberg
Название: Willful Ignorance: The Mismeasure of Uncertainty
ISBN: 0470890444 ISBN-13(EAN): 9780470890448
Издательство: Wiley
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Цена: 30570.00 T
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Описание: This provocative new book posits how the tacit principle of "willful ignorance" has led to a deep divide between qualitative and quantitative modes of research that will increasingly constrain scientific progress unless bridged by a broadened conception of statistical methodology.

Автор: Compte Olivier, Postlewaite Andrew
Название: Ignorance and Uncertainty
ISBN: 1108434495 ISBN-13(EAN): 9781108434492
Издательство: Cambridge Academ
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Цена: 35910.00 T
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Описание: Compte and Postlewaite propose novel methods to incorporate ignorance and uncertainty into economic modeling, without complex mathematics. An accessible text that proposes a constructive critique of the discipline, and that will find a broad audience with readers who build or use economic models, and those just interested in the discipline.

Автор: Pratiksha Saxena, Dipti Singh, Millie Pant
Название: Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications
ISBN: 1466698853 ISBN-13(EAN): 9781466698857
Издательство: Mare Nostrum (Eurospan)
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Цена: 218990.00 T
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Описание: Presents the latest research trends and developments in the area of applied optimization methodologies and soft computing techniques for solving complex problems. Taking a multi-disciplinary approach, this critical publication is an essential reference source for engineers, managers, researchers, and post-graduate students.

Автор: Coes, Don (university Of New Mexico, Usa)
Название: Impact of price uncertainty
ISBN: 1138633631 ISBN-13(EAN): 9781138633636
Издательство: Taylor&Francis
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Цена: 34700.00 T
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Описание: Originally published in 1979. This is an important early study into the significance of uncertainty.

Автор: Simona Salicone
Название: Measurement Uncertainty
ISBN: 1441940340 ISBN-13(EAN): 9781441940346
Издательство: Springer
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Цена: 75420.00 T
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Описание: This book presents an alternative approach and companion to the GUM Instrumentation Standard. Coverage provides an overview of the current standard, then pinpoints and constructively resolves its limitations.

Автор: Kurt Weichselberger; Sigrid P?hlmann
Название: A Methodology for Uncertainty in Knowledge-Based Systems
ISBN: 3540523367 ISBN-13(EAN): 9783540523369
Издательство: Springer
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Цена: 21420.00 T
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Описание: Proposes the use of probability theory in handling uncertainty in expert systems. This book demonstrates the superiority of consequent probabilistic methods for handling and combining uncertainty in expert systems, compared with well known rules like the Dempster-Shafer rule or the MYCIN rule.

Автор: Ehsan Goodarzi; Mina Ziaei; Lee Teang Shui
Название: Introduction to Risk and Uncertainty in Hydrosystem Engineering
ISBN: 9400758502 ISBN-13(EAN): 9789400758506
Издательство: Springer
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Цена: 121890.00 T
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Описание: This book presents the basics of stochastic, risk and uncertainty analysis and random sampling techniques using practical examples, solved step by step. Includes appropriate Excel functions as an alternative to solve the examples, and two real case studies.

Автор: Johnathan M. Bardsley
Название: Computational Uncertainty Quantification for Inverse Problems
ISBN: 1611975379 ISBN-13(EAN): 9781611975376
Издательство: Mare Nostrum (Eurospan)
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Цена: 53090.00 T
Наличие на складе: Невозможна поставка.
Описание: This book is an introduction to both computational inverse problems and uncertainty quantification (UQ) for inverse problems. The book also presents more advanced material on Bayesian methods and UQ, including Markov chain Monte Carlo sampling methods for UQ in inverse problems. Each chapter contains MATLAB® code that implements the algorithms and generates the figures, as well as a large number of exercises accessible to both graduate students and researchers. Computational Uncertainty Quantification for Inverse Problems is intended for graduate students, researchers, and applied scientists. It is appropriate for courses on computational inverse problems, Bayesian methods for inverse problems, and UQ methods for inverse problems.

Автор: Hu
Название: Engineering Design under Uncertainty and Health Prognostics
ISBN: 3319925725 ISBN-13(EAN): 9783319925721
Издательство: Springer
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Цена: 167700.00 T
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Описание: This book presents state-of-the-art probabilistic methods for the reliability analysis and design of engineering products and processes.

Автор: Mohammed Abdellaoui; John D. Hey
Название: Advances in Decision Making Under Risk and Uncertainty
ISBN: 3642088007 ISBN-13(EAN): 9783642088001
Издательство: Springer
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Цена: 139750.00 T
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Описание: Uncertainty and Information Modeling.- Revealed Ambiguity and Its Consequences: Updating.- Dynamic Decision Making When Risk Perception Depends on Past Experience.- Representation of Conditional Preferences Under Uncertainty.- Subjective Information in Decision Making and Communication.- Risk Modeling.- Sensitivity Analysis in Decision Making: A Consistent Approach.- Alternation Bias and the Parameterization of Cumulative Prospect Theory.- Proposing a Normative Basis for the S-Shaped Value Function.- Experimental Individual Decision Making.- Individual Choice from a Convex Lottery Set: Experimental Evidence.- Temptations and Dynamic Consistency.- Monty Hall's Three Doors for Dummies.- Overconfidence in Predictions as an Effect of Desirability Bias.- Experimental Interactive Decision Making.- Granny Versus Game Theorist: Ambiguity in Experimental Games.- Guessing Games and People Behaviours: What Can We Learn?.- The Determinants of Individual Behaviour in Network Formation: Some Experimental Evidence.