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Improved Elman neural network and its application

A novel improved hysteretic Elman neural network which contains input layer, hidden layer, output layer and context layer is proposed to enhance the short-term forecasting accuracy of wind speed series. The activation of functions in the hidden layer are chosen as the hysteretic activation, and other activation functions are chosen Sigmoid functions. The hysteretic activation function has two response branches: the rising branch and the falling branch. The output response of the neuron is determined by the current input states and variation tendencies. Therefore, the neuron must store its historical state information which can enhance the information utilization rate of the neural network and improve the information process ability. Chaos optimization algorithm is used to train the connection weights and hysteretic parameters. The improved Elman neural network is used to predict the wind speed series. Experiment results show that the improved Elman neural network can improve the prediction performance, and more effective prediction results can be got by the network.