基于粗糙近似的区间值模糊形式背景属性约简  

Attribute reduction of interval-valued fuzzy formal contexts based on rough approximations

作　　者：李同军 孟琦峰 吴伟志 LI Tongjun;MENG Qifeng;WU Weizhi(College of Information Engineering,Zhejiang Ocean University,Zhoushan 316022,China)

机构地区：[1]浙江海洋大学信息工程学院,浙江舟山316022

出　　处：《西北大学学报(自然科学版)》2025年第2期333-342,共10页Journal of Northwest University(Natural Science Edition)

基　　金：国家自然科学基金(12371466)。

摘　　要：将粗造集技术融入形式概念分析是数据分析和信息处理的一种重要方法,其对数据知识发现具有重要意义。在区间值模糊形式背景中定义两种粗糙近似算子,从而导出一种新型单边概念格,即经典-区间值模糊概念格,主要研究新型概念格的属性约简。给出区间值模糊形式背景属性约简和差别矩阵的定义,研究协调属性集判定和约简计算方法。给出协调属性集判定定理和基于差别矩阵的约简计算方法。新概念模型可为区间值模糊形式背景中的知识发现提供新方法,给出的约简方法有利于开发高效的属性约简算法。The integration of rough sets into formal concept analysis is an important method for data analysis and information processing,which is of great significance for data knowledge discovery.Two rough approximation operators are defined in an interval-valued fuzzy formal context,and a new type of one-side concept lattice,namely,crisp-interval-valued fuzzy concept lattice,is derived,and its attribute reduction is meanly studied.According to the definition of attribute reduction of interval-valued fuzzy formal context,the judgement of consistent attribute sets is considered,and by using the techniques of discernibility matrix of rough sets,the calculation method of reducts is explored.The new concept model can provide new approaches for the knowledge discovery of interval-valued fuzzy formal contexts,and the obtained reduction method is beneficial to develop efficient attribute reduction algorithms.

关 键 词：区间值模糊形式背景 经典-区间值模糊概念格 属性约简 区间值模糊集 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]