Research On Fuzzy Neural Network Models And Its Application

Fuzzy neural network is an important research problem in the domain of intelligent control. FNN is composed of the neural network and fuzzy logic system. It is the organic integration of two parts. FNN can deal with the abstract information, such as the language information. It is good at self-learning and self-tuning. So the theory of FNN is very important for the intelligent control. So in this paper, the research status on FNN and their shortage are introduced. The advantages and the shortages of integration method for fuzzy logic and neural network are analyzed and compared. This paper analyses the interrelated basic theory of FNN, then researches two fuzzy neural networks, and gives the result of experiment. Then according to the inner relationship between the neural network and fuzzy logic inference, a new fuzzy neural network, with effective algorithm and structure, can be obtained. It can be proved to approximate at any degree of accuracy to any real continuous function in a compact domain by using the famous stone-Weirstrass law. This paper executes software simulation and analysis the result by the new fuzzy neural network. It shows the method is effective and feasible. This paper designs a fuzzy neural network control strategy, simulation experiment shows the feasibility of this control strategy. Finally, a summary is given in the 6^th section and the future research directions are also pointed out.