A Weighted Interval-Valued Fuzzy Decision Method Based on OWA Operator

Abstract

This paper presents a weighted interval-valued fuzzy(IvF) reasoning algorithm based on OWA operator for handling decision making problem where interval-valued fuzzy set(IvFS) theory and IvF production rules are used for uncertain knowledge representation. The proposed algorithm can perform IvF matching between the unknown model and the antecedent portion of IvF rule by employing a weighted similarity measure to determine the presence of decision model with a confidence interval. Finally, One application example in medical diagnosis illustrates the proposed method is very flexible, reasonable and can be executed efficiently.