TY - JOUR
T1 - Rough set-based logics for multicriteria decision analysis
AU - Fan, Tuan Fang
AU - Liu, Duen-Ren
AU - Tzeng, Gwo Hshiung
PY - 2007/10/1
Y1 - 2007/10/1
N2 - In this paper, we propose some decision logic languages for rule representation in rough set-based multicriteria analysis. The semantic models of these logics are data tables, each of which is comprised of a finite set of objects described by a finite set of criteria/attributes. The domains of the criteria may have ordinal properties expressing preference scales, while the domains of the attributes may not. The validity, support, and confidence of a rule are defined via its satisfaction in the data table.
AB - In this paper, we propose some decision logic languages for rule representation in rough set-based multicriteria analysis. The semantic models of these logics are data tables, each of which is comprised of a finite set of objects described by a finite set of criteria/attributes. The domains of the criteria may have ordinal properties expressing preference scales, while the domains of the attributes may not. The validity, support, and confidence of a rule are defined via its satisfaction in the data table.
KW - Artificial intelligence
KW - Decision logic
KW - Fuzzy sets
KW - Multicriteria decision analysis
KW - Rough sets
UR - http://www.scopus.com/inward/record.url?scp=34147138297&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2006.08.029
DO - 10.1016/j.ejor.2006.08.029
M3 - Article
AN - SCOPUS:34147138297
SN - 0377-2217
VL - 182
SP - 340
EP - 355
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 1
ER -