SIRMs connected fuzzy inference method adopting emphasis and suppression

The single input rule modules connected fuzzy inference method (SIRMs method) can decrease the number of fuzzy rules drastically in comparison with the conventional fuzzy inference methods. However, the inference results obtained by the SIRMs method is generally simple compared with those of the conventional fuzzy inference methods. For example, the SIRMs method may be not equivalent to the product–sum-gravity method and fuzzy singleton-type inference method, if the fuzzy sets of the antecedent parts are limited to normal fuzzy sets. In this paper, we propose a fuzzy singleton-type SIRMs method, which weights the rules of the SIRMs method, in order to solve the above problem. This paper also clarifies the property of the fuzzy singleton-type SIRMs method, from the view point of equivalence and monotonicity. Moreover, the fuzzy singleton-type SIRMs method is shown to be superior to the conventional SIRMs method by applying to a medical diagnosis system.