Dominance-based fuzzy rough set analysis of uncertain and possibilistic data tables

被引:41
作者
Fan, Tuan-Fang [2 ]
Liau, Churn-Jung [1 ]
Liu, Duen-Ren [3 ]
机构
[1] Acad Sinica, Inst Informat Sci, Taipei 115, Taiwan
[2] Natl Penghu Univ Sci & Technol, Dept Comp Sci & Informat Engn, Penghu 880, Taiwan
[3] Natl Chiao Tung Univ, Inst Informat Management, Hsinchu 300, Taiwan
关键词
Dominance-based rough set approach; Multi-criteria decision analysis; Preference-ordered data tables; Rough set theory; Uncertain data tables; Possibilistic data table; APPROXIMATION; LOGIC;
D O I
10.1016/j.ijar.2011.01.009
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a dominance-based fuzzy rough set approach for the decision analysis of a preference-ordered uncertain or possibilistic data table, which is comprised of a finite set of objects described by a finite set of criteria. The domains of the criteria may have ordinal properties that express preference scales. In the proposed approach, we first compute the degree of dominance between any two objects based on their imprecise evaluations with respect to each criterion. This results in a valued dominance relation on the universe. Then, we define the degree of adherence to the dominance principle by every pair of objects and the degree of consistency of each object. The consistency degrees of all objects are aggregated to derive the quality of the classification, which we use to define the reducts of a data table. In addition, the upward and downward unions of decision classes are fuzzy subsets of the universe. Thus, the lower and upper approximations of the decision classes based on the valued dominance relation are fuzzy rough sets. By using the lower approximations of the decision classes, we can derive two types of decision rules that can be applied to new decision cases. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:1283 / 1297
页数:15
相关论文
共 36 条
[11]  
DUBOIS D, 1994, IEEE INTELL SYST APP, V9, P15
[12]  
Dubois D., 2009, Decision-Making Process, P85, DOI [DOI 10.1002/9780470611876.CH3, 10.1002/9780470611876.ch3]
[13]   Rough set-based logics for multicriteria decision analysis [J].
Fan, Tuan-Fang ;
Liu, Duen-Ren ;
Tzeng, Gwo-Hshiung .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 182 (01) :340-355
[14]   Axiomatic characterization of a general utility function and its particular cases in terms of conjoint measurement and rough-set decision rules [J].
Greco, S ;
Matarazzo, B ;
Slowinski, R .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2004, 158 (02) :271-292
[15]  
Greco S, 2000, INFOR, V38, P161
[16]   Rough approximation of a preference relation by dominance relations [J].
Greco, S ;
Matarazzo, B ;
Slowinski, R .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1999, 117 (01) :63-83
[17]   Rough sets methodology for sorting problems in presence of multiple attributes and criteria [J].
Greco, S ;
Matarazzo, B ;
Slowinski, R .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2002, 138 (02) :247-259
[18]  
Greco S, 2000, APPL OPTIM, V45, P295
[19]   Rough sets theory for multicriteria decision analysis [J].
Greco, S ;
Matarazzo, B ;
Slowinski, R .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2001, 129 (01) :1-47
[20]   Fuzzy preference based rough sets [J].
Hu, Qinghua ;
Yu, Daren ;
Guo, Maozu .
INFORMATION SCIENCES, 2010, 180 (10) :2003-2022