In order to determine the feed-forward neural network-s structure

fuzzy feed-forward neural network was constructed based on the sampling data

which reflected the system-s information contained in the construction data. And the hidden layer neuron activation function is the product of triangular membership function and corresponding data output. For this model

the network-s structure can be adjusted with the change of sampling data for designer

and the best weight was received based on weights-direct-determination. Numerical simulation results show that the fuzzy feed-forward neural network has many advantages such as high approximation precision

and the structure can be adjusted with good prediction and high real-time. It is better than the other feed-forward neural networks.