模糊距离与模糊范数

Masamichi Kon
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引用次数: 0

摘要

我们考虑度量、向量或赋范空间上的模糊集。不假定模糊集具有紧支撑。本文提出了一个模糊距离和一个模糊范数来度量两个模糊集之间的差,并研究了它们的基本性质。它们的定义是基于Zadeh的可拓原理。尽管它们不同于基于豪斯多夫度量的经典度量,但它们适用于包含不确定性或模糊性的数据。当数据被表示为模糊集时,所获得的结果可以被期望用于分析这样的数据。
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FUZZY DISTANCE AND FUZZY NORM
We consider fuzzy sets on a metric, vector, or normed space. It is not assumed that the fuzzy sets have compact supports. In the present paper, a fuzzy distance and a fuzzy norm are proposed in order to measure the difference between two fuzzy sets, and their fundamental properties are investigated. Their definitions are based on Zadeh’s extension principle. Although they are different from the classical ones based on the Hausdorff metric, they are suitable for data containing uncertainty or vagueness. The obtained results can be expected to be useful for analyzing such data when the data are represented as fuzzy sets.
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来源期刊
Journal of the Operations Research Society of Japan
Journal of the Operations Research Society of Japan 管理科学-运筹学与管理科学
CiteScore
0.70
自引率
0.00%
发文量
12
审稿时长
12 months
期刊介绍: The journal publishes original work and quality reviews in the field of operations research and management science to OR practitioners and researchers in two substantive categories: operations research methods; applications and practices of operations research in industry, public sector, and all areas of science and engineering.
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