在代用模型中使用新方法比较模糊数的百分比

IF 3.6 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Fuzzy Systems Pub Date : 2024-06-04 DOI:10.1007/s40815-024-01732-0
Thomas Oberleiter, Kai Willner
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引用次数: 0

摘要

这里介绍的 O 指数可以说明两个模糊数之间的偏差百分比。为此,一个模糊数被定义为参考值。借助其核心值和支持度来描述这个模糊数。另一个模糊数被定义为比较数,其偏差通过两个数的左右界限的面积差来量化。此外,还考虑到了涉及分解模糊数的情况,分解模糊数是以\(\α \)-切分给出的。因此,O-index-\(\alpha \)-cut可以用来计算每个\(\alpha \)-cut的单独百分比偏差,从而产生额外的知识。O-index 可以非常详细地描述两个模糊数之间的偏差。O-index 的一个应用是在不确定性量化的背景下,估计代用模型相对于参考模型的准确性。下面以弯曲梁这一机械模型为例进行说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Percentage Comparison of Fuzzy Numbers Using a Newly Presented Method in the Context of Surrogate Modeling

The O-index presented here allows a statement about the percentage deviation between two fuzzy numbers. For this purpose, one fuzzy number is defined s the reference. This fuzzy number is described with the help of its core value and its support. The deviation of the other fuzzy number, which is defined as the comparison number, is then quantified via the area differences of the left and right limits of the two numbers. In addition, the case when decomposed fuzzy numbers are involved, which are given as \(\alpha \)-cuts is taken into account. Thus, the O-index-\(\alpha \) can be used to calculate a separate percentage deviation for each \(\alpha \)-cut and thus generate additional knowledge. The O-index then allows a very detailed description of the deviation between two fuzzy numbers. One application of the O-index is the estimation of the accuracy of a surrogate model in relation to a reference model in the context of uncertainty quantification. This is illustrated by a mechanical example, a bending beam.

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来源期刊
International Journal of Fuzzy Systems
International Journal of Fuzzy Systems 工程技术-计算机:人工智能
CiteScore
7.80
自引率
9.30%
发文量
188
审稿时长
16 months
期刊介绍: The International Journal of Fuzzy Systems (IJFS) is an official journal of Taiwan Fuzzy Systems Association (TFSA) and is published semi-quarterly. IJFS will consider high quality papers that deal with the theory, design, and application of fuzzy systems, soft computing systems, grey systems, and extension theory systems ranging from hardware to software. Survey and expository submissions are also welcome.
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