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Titlebook: Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications; Andrew Pownuk,Vladik Kreinovich Book 2018 S

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發(fā)表于 2025-3-21 16:17:20 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
編輯Andrew Pownuk,Vladik Kreinovich
視頻videohttp://file.papertrans.cn/231/230091/230091.mp4
概述Presents successful methods for estimating the accuracy of the results of data processing under different models of measurement and estimation inaccuracies: probabilistic, interval, and fuzzy.Offers m
叢書(shū)名稱Studies in Computational Intelligence
圖書(shū)封面Titlebook: Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications;  Andrew Pownuk,Vladik Kreinovich Book 2018 S
描述How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc..In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty..The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty.?.
出版日期Book 2018
關(guān)鍵詞Computational Intelligence; Interval Uncertainty; Uncertainty; Probabilistic Uncertainty; Fuzziness
版次1
doihttps://doi.org/10.1007/978-3-319-91026-0
isbn_softcover978-3-030-08158-4
isbn_ebook978-3-319-91026-0Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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發(fā)表于 2025-3-21 22:34:27 | 只看該作者
1860-949X on inaccuracies: probabilistic, interval, and fuzzy.Offers mHow can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at su
板凳
發(fā)表于 2025-3-22 01:42:30 | 只看該作者
Soap Operas, Women and the Nation,ase of decision making in conflict situations is analyzed in Sect.?.. In Sect.?., we consider decision making under probabilistic uncertainty and in Sect.?., we consider the case of general uncertainty.
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發(fā)表于 2025-3-22 06:19:36 | 只看該作者
Decision Making Under Uncertainty,ase of decision making in conflict situations is analyzed in Sect.?.. In Sect.?., we consider decision making under probabilistic uncertainty and in Sect.?., we consider the case of general uncertainty.
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發(fā)表于 2025-3-22 10:59:58 | 只看該作者
https://doi.org/10.1007/978-3-658-02376-8m min, a similar speedup is described in Sect.?.. In Sect.?., we describe a speedup for the case of probabilistic uncertainty. Finally, in Sect.?., we speculate on the possibility of use quantum computing to further speed up data processing.
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發(fā)表于 2025-3-22 17:06:12 | 只看該作者
How to Speed Up Computations,m min, a similar speedup is described in Sect.?.. In Sect.?., we describe a speedup for the case of probabilistic uncertainty. Finally, in Sect.?., we speculate on the possibility of use quantum computing to further speed up data processing.
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發(fā)表于 2025-3-22 21:50:48 | 只看該作者
Towards a Better Understandability of Uncertainty-Estimating Algorithms,we explain why it is reasonable to consider mixtures of probability distributions. In Sect.?., we consider the case of fuzzy uncertainty; we explain why seemingly non-traditional fuzzy ideas are, in effect, very similar to the ideas from traditional logic.
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發(fā)表于 2025-3-23 04:40:43 | 只看該作者
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Combining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications
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