Title :
A comparative study of belief and plausibility reducís in information systems with fuzzy decisions
Author_Institution :
Sch. of Math., Phys. & Inf. Sci., Zhejiang Ocean Univ., Zhoushan, China
Abstract :
Knowledge reduction is one of the main problems in the study of rough set theory. This paper deals with attribute reduction in complete information systems with fuzzy decisions. The concepts of lower approximation reducts, upper approximation reducts, belief reducts, and plausibility reducts in information systems with fuzzy decisions are introduced and their relationships are examined. It is shown that, in a complete information system with fuzzy decisions, an attribute set is a belief reduct (a plausibility reduct, respectively) if and only if it is a lower approximation reduct (an upper approximation reduct, respectively).
Keywords :
fuzzy set theory; information systems; rough set theory; attribute reduction; belief reducts; fuzzy decisions; information systems; knowledge reduction; lower approximation reducts; plausibility reducts; rough set theory; upper approximation reducts; Educational institutions; Belief functions; consistent sets; information systems; information systems with fuzzy decisions; reducts; rough sets;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580481
