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Titlebook: Introduction to Uncertainty Quantification; T.J. Sullivan Textbook 2015 Springer International Publishing Switzerland 2015 Computational p

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書(shū)目名稱(chēng)Introduction to Uncertainty Quantification
編輯T.J. Sullivan
視頻videohttp://file.papertrans.cn/475/474301/474301.mp4
概述One of the first textbooks on the mathematics and statistics of uncertainty quantification.Complete with examples and exercises throughout.Comprehensive with rigorous mathematical details and proofs,
叢書(shū)名稱(chēng)Texts in Applied Mathematics
圖書(shū)封面Titlebook: Introduction to Uncertainty Quantification;  T.J. Sullivan Textbook 2015 Springer International Publishing Switzerland 2015 Computational p
描述.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..T. J. Sullivan. was Warwick Zeeman Lecturer at the Mathematics Institute
出版日期Textbook 2015
關(guān)鍵詞Computational probability; Distributional robustness; Inverse Problems; Model order reduction; Sensitivi
版次1
doihttps://doi.org/10.1007/978-3-319-23395-6
isbn_softcover978-3-319-79478-5
isbn_ebook978-3-319-23395-6Series ISSN 0939-2475 Series E-ISSN 2196-9949
issn_series 0939-2475
copyrightSpringer International Publishing Switzerland 2015
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Orthogonal Polynomials and Applications, a central role in numerical integration using quadrature rules (Chapter 9) and approximation theory; in the context of UQ, they are also a foundational tool in polynomial chaos expansions (Chapter 11).
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Distributional Uncertainty, distributions involved are known and can be sampled. In practice, however, such assumptions about probability distributions are always wrong to some degree: the distributions used in practice may only be simple approximations of more complicated real ones, or there may be significant uncertainty ab
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T. J. Sullivanntal reference work. Over the past twenty years, the field of production and operations management has grown more rapidly than ever and consequently its boundaries have been stretched in all directions. For example, in the last two decades, production and manufacturing management absorbed in rapid s
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T. J. Sullivanntal reference work. Over the past twenty years, the field of production and operations management has grown more rapidly than ever and consequently its boundaries have been stretched in all directions. For example, in the last two decades, production and manufacturing management absorbed in rapid s
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