Abstract
Most studies on tuning of fuzzy inference are concerned with numerical inputs and outputs only, and very few research has been done on tuning of fuzzy inference with fuzzy inputs and outputs. Moreover, in many cases the objects of tuning are fuzzy predicates only, apart from the other factors intervening in fuzzy inference. In this paper we propose a method to tune the fuzzy inference when teaching signals are given as fuzzy sets. The objects of tuning are the parameters of aggregation operators, implication functions and combination functions, which are important factors of the fuzzy inference method, as well as the parameters of fuzzy predicates. In the proposed method, we adjust the value of the parameters by the gradient descent method, using the network representing the calculation process of the fuzzy inference.
