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Fuzzy-Valued Transitive Inclusion Measure, Similarity Measure and Application to Approximate Reasoning

机译:模糊值传递包含度量,相似度量及其在近似推理中的应用

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In fuzzy set theory, inclusion measure indicates the degree to which a given fuzzy set is contained in another fuzzy set. Many inclusion measures taking values in [0,1] have been made in the literature. This paper proposes a series of fuzzy-valued inclusion measures which, by a relation view, are reflexive, antisymmetric and J-transitive where J is a left-continuous triangular norm; In addition, they possess most of the axiomatic properties which are postulated by Sinha and Dougherty for an inclusion measure. Fuzzy-valued similarity measures are also defined by the fuzzy-valued inclusion measures; They have J-transitivity and properties introduced by Liu for a similarity measure. Lastly two methods for inference in approximate reasoning based on the fuzzy-valued inclusion measure and the fuzzy-valued similarity measure are studied.
机译:在模糊集理论中,包含度量表示给定的模糊集包含在另一个模糊集中的程度。文献中已经有很多采用[0,1]中的值的包含度量。本文提出了一系列模糊值包含度量,从关系的角度来看,它们是自反的,反对称的和J可传递的,其中J是左连续的三角形范数;此外,它们具有Sinha和Dougherty提出的用于包容性测量的大多数公理特性。模糊值相似性度量也由模糊值包含度量定义。它们具有J-可及性和Liu引入的用于相似度的特性。最后研究了基于模糊值包含测度和模糊值相似度测度的两种推理方法。

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