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Titlebook: Bounding Uncertainty in Civil Engineering; Theoretical Backgrou Alberto Bernardini,Fulvio Tonon Book 2010 Springer-Verlag Berlin Heidelberg

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發(fā)表于 2025-3-21 19:06:31 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Bounding Uncertainty in Civil Engineering
期刊簡(jiǎn)稱Theoretical Backgrou
影響因子2023Alberto Bernardini,Fulvio Tonon
視頻videohttp://file.papertrans.cn/191/190075/190075.mp4
發(fā)行地址Basic ideas and methods of Random Sets in Civil Engineering are presented with the aid of simple worked-out examples and suggested problems.Useful as reference for practicing engineers involved in pla
圖書封面Titlebook: Bounding Uncertainty in Civil Engineering; Theoretical Backgrou Alberto Bernardini,Fulvio Tonon Book 2010 Springer-Verlag Berlin Heidelberg
影響因子Taking an engineering, rather than a mathematical, approach, Bounding uncertainty in Civil Engineering - Theoretical Background deals with the mathematical theories that use convex sets of probability distributions to describe the input data and/or the final response of systems. The particular point of view of the authors is centered on the applications to civil engineering problems, and the theory of random sets has been adopted as a basic and relatively simple model. However, the authors have tried to elucidate its connections to the more general theory of imprecise probabilities, Choquet capacities, fuzzy sets, p-boxes, convex sets of parametric probability distributions, and approximate reasoning both in one dimension and in several dimensions with associated joint spaces. If choosing the theory of random sets may lead to some loss of generality, it has, on the other hand, allowed for a self-contained selection of the topics and a more unified presentation of thetheoretical contents and algorithms. With over 80 examples worked out step by step, the book should assist newcomers to the subject (who may otherwise find it difficult to navigate a vast and dispersed literature) in ap
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Book 2010r a self-contained selection of the topics and a more unified presentation of thetheoretical contents and algorithms. With over 80 examples worked out step by step, the book should assist newcomers to the subject (who may otherwise find it difficult to navigate a vast and dispersed literature) in ap
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Book 2010tical theories that use convex sets of probability distributions to describe the input data and/or the final response of systems. The particular point of view of the authors is centered on the applications to civil engineering problems, and the theory of random sets has been adopted as a basic and r
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Approximate Reasoning,ed with both probabilistic procedures and fuzzy set operations..Finally it will be shown in Section 6.5 that fuzzy logic gives powerful, simple and robust procedures in the field of pattern recognition, clustering and optimal choices in decision making.
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