AN EFFICIENT METHOD OF FUZZY RULES GENERATION

A method for automatic generation of fuzzy rules is proposed, which finds out the essential points of the control surface by the concept of K Nearest Neighbor, and then uses these points to determine the fuzzy partitions so that it can construct a fuzzy neural network to learn fuzzy rules. The learning algorithm of the neural network is BP algorithm. During the training, the network can increase the number of fuzzy partitions properly due to the condition of the convergence, and then reconstructs itself to learn again. This method can generate a simple and effective rule set, and has a good convergent condition as well as a fast convergent speed.