A fuzzy neural networks technique with fast backpropagation learning

A fuzzy neural network (FNN) technique is presented based on fuzzy systems and neural network technologies. Utilizing human knowledge and expertise, the FNN technique is applied to accelerate the learning process of a novel backpropagation algorithm in which both self-adjusting activation and learning rate functions are designated. The learning speed and quality of the fuzzy neural networks are proved to be superior to those of standard backpropagation and other methods using changeable learning rates or activation functions. The proposed networks are currently developed and implemented in a C language environment. Experimental and analytical results demonstrate that the FNN technique is a novel and potentially powerful approach to intelligent neural networks.<>