Abstract
This paper proposes a fuzzy-arithmetic-based method for extracting fuzzy if-then rules from a multi-layer feedforward neural network. We assume that the neural network has already been trained for a multi-dimensional pattern classification problem. The proposed method extracts fuzzy if-then rules such as "If x_1 is small and x_2 is large then Class 2 with CF=0.9" where CF is the grade of certainty of this rule. For extracting such a fuzzy if-then rule, first antecedent fuzzy sets of a fuzzy if-then rule are presented to the trained neural network in the proposed method. Next the outputs from the neural network are calculated as fuzzy numbers based on fuzzy arithmetic. Then the consequent class and the grade of certainty of the fuzzy if-then rule are determined by an inequality relation between the fuzzy number outputs. In order to show the effectiveness of the proposed method, we show simulation results on some numerical examples.
