Abstract
This paper proposes the situation-dependent membership function estimation method based on analogical reasoning. The proposed method defines the relation between membership functions representing same category in different situations as a function, which is called analogy. If membership functions expressing same categories in different situations are already identified, analogy can be identified by them, and other membership functions in the situation can be estimated by analogical reasoning. This paper also confirms effectiveness of the proposed method experimentally. (1) The relations between membership functions in different situations are expressed by some degree polynomials in preliminary experiments and those polynomials are analyzed to obtain the appropriate degree of polynomials as analogy. (2) Situation-dependent membership functions estimated by analogical reasoning are compared with those identified by other method.
