面向决策分析的多粒度计算模型与方法综述  

Review on Multi-granulation Computing Models and Methods for Decision Analysis

作　　者：庞继芳[1] 宋鹏[2] 梁吉业[1,3] PANG Jifang;SONG Peng;LIANG Jiye(School of Computer and Information Technology,Shanxi University,Taiyuan 030006;School of Economics and Management,Shanxi University,Taiyuan 030006;Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education,Shanxi University,Taiyuan 030006)

机构地区：[1]山西大学计算机与信息技术学院,太原030006 [2]山西大学经济与管理学院,太原030006 [3]山西大学计算智能与中文信息处理教育部重点实验室,太原030006

出　　处：《模式识别与人工智能》2021年第12期1120-1130,共11页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.62006148);山西省重点研发计划项目(No.201903D121162)资助。

摘　　要：作为粒计算研究方向的核心概念和关键技术,多粒度计算强调对现实世界问题多视角、多层次的理解和描述,可获得合理、满意的求解结果.为了深化多粒度计算与决策分析的有效融合,更好地满足人们的实际决策需求,文中首先介绍多粒度粗糙集、多尺度数据分析、序贯三支决策、分层分类学习四类多粒度计算模型,并阐述各自的主要特点及发展过程.进而从属性约简、规则提取、粒度选择、信息融合、群决策、多属性群决策、分类决策、动态决策等方面总结基于多粒度计算模型的决策分析方法研究现状.最后,对大数据时代智能决策领域中若干具有挑战性的研究方向进行展望,以期推动多粒度智能决策的不断发展与创新.As the core concept and key technology of granular computing,multi-granulation computing emphasizes multi-view and multi-level understanding and description of real-world problems to obtain more reasonable and satisfactory results.The existing four types of multi-granulation computing models are firstly introduced,including multi-granulation rough set,multi-scale data analysis,sequential three-way decision and hierarchical classification learning,for the further effective fusion of multi-granulation computing and decision analysis and better satisfaction with actual decision-making needs.Then,their main characteristics and development process are expounded.Furthermore,the research status of decision analysis methods based on multi-granulation computing models is summarized from the aspects of attribute reduction,rule extraction,granularity selection,information fusion,group decision-making,multi-attribute group decision-making,classification decision-making and dynamic decision-making.Finally,some challenging research directions of intelligent decision-making in the era of big data are forecasted to promote the continuous development and innovation of multi-granulation intelligent decision-making.

关 键 词：多粒度粗糙集 多尺度数据分析 序贯三支决策 分层分类学习 决策分析 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]