Determining the Rules for Computing Fixpoints and Introduction of Min-generated Fuzzy Concepts from a Fuzzy Context

Partha Ghosh
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Abstract

In theory of fuzzy concept lattice, generating fuzzy concepts from a given data with fuzzy attributes is one of the fundamental problem. Since fuzzy concepts are the fixpoints of a particular fuzzy operator that is associated with input data, the problem of generating fuzzy concepts turn out to be the problem of computing all fixpoints of this operator. In this article, we have established ten rules for generating fixpoints of two fuzzy closure operators, \(\uparrow\downarrow\) and \(\downarrow\uparrow\). Then unifying all the proposed rules, we present a new method and algorithm for computing fixpoints (fuzzy concepts) which are defined as min-generated fuzzy concepts.
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确定不动点计算规则及模糊环境中最小生成模糊概念的引入
在模糊概念格理论中,从具有模糊属性的给定数据生成模糊概念是一个基本问题。由于模糊概念是与输入数据相关联的特定模糊算子的不动点,因此生成模糊概念的问题就变成了计算该算子的所有不动点的问题。在本文中,我们建立了10条规则,用于生成两个模糊闭包操作符\(\uparrow\downarrow\)和\(\downarrow\uparrow\)的不动点。在此基础上,提出了一种新的计算不动点(模糊概念)的方法和算法,将不动点定义为最小生成模糊概念。
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