Fuzzy singleton-type SIC fuzzy inference model

This paper firstly proposes a fuzzy singleton-type Single Input Connected fuzzy inference model (fuzzy singleton-type SIC model) which attaches weights to the rules of the conventional SIC model. Second, it shows the property of the proposed model from the point of view of the equivalence. Thirdly, the learning algorithm of the fuzzy singleton-type SIC model is derived by using steepest descent method. Finally, the proposed model is applied to medical diagnosis, and compared with the conventional fuzzy inference model. From the above results, the applicability of the proposed model is clarified.