Chaos optimization design for a fuzzy-neural network structure
一类模糊神经网络结构的混沌优化设计

An optimization design method was proposed for a Fuzzy-Neural Network (FNN) structure based on chaotic variables. Chaotic variables were applied to the search of FNN structure and all parameters, which made fuzzy rule numbers and all parameters be in chaotic state. All FNN structure was variable, a FNN was found according to minimum performance standard. The defuzzification part right parameters of FNN were adjusted by the least square method on line. Simulation results show FNN by using the method has simpler structure and higher control precision.