模糊信息粒化理论及应用研究综述  

Fuzzy information granulation: review of theory and applications

作　　者：汤雨晴 于福生[1] TANG Yuqing;YU Fusheng(School of Mathematical Sciences,Beijing Normal University,100875,Beijing,China)

机构地区：[1]北京师范大学数学科学学院,北京100875

出　　处：《北京师范大学学报（自然科学版）》2022年第3期349-361,共13页Journal of Beijing Normal University(Natural Science)

基　　金：国家自然科学基金资助项目(11971065,11571001)。

摘　　要：信息粒化因模拟人类分析处理复杂问题的方式而受到广泛关注.基于模糊集理论、粗糙集理论及商空间理论等典型信息粒化理论及方法的研究已取得长足的发展,其中基于模糊集的信息粒化理论及方法旨在应对普遍存在的具有模糊性的问题和现象.本文综述模糊信息粒化理论与方法的建立及发展过程,梳理模糊信息粒化研究成果的系统体系结构,总结其在聚类、预测和关联规则挖掘等重要领域的应用,以促进该领域的研究.Information granulation has attracted much attention for simulating the way humans analyze and deal with complex problems. Considerable strides have been made on theory and method of information granulation,typically based on fuzzy set theory, rough set theory, quotient space theory and so on, where fuzzy information granulation aims at handling problems and phenomena with fuzziness. In this paper we review establishment and development of fuzzy information granulation, sort out systematic structure of fuzzy information granulation. We summarize the extensive applications of fuzzy information granulation in fields such as clustering,forecasting and association rules mining.

关 键 词：信息粒化 模糊信息粒化 聚类 预测 关联规则挖掘 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]