Hysteretic Neural Network and Its Application in the Prediction of the Wind Speed Series
In order to improve the information processing capabilities of the traditional neural network,and improve the forecast accuracy of the wind speed series,a new hysteretic neural network based on the hysteretic neurons is proposed.The hysteretic neuron is constructed by adding a hysteretic operator into the activation function.The hysteretic characteristic can make the response of the neuron is related to not only the current input information but also the history input information.In this way,the amount of information used in the prediction process is increased,and the prediction ability of the neural network can be improved.In order to avoid the information redundancy or loss,the structure and the training samples are determined according to the autocorrelation function and the partial autocorrelation function of the wind speed series.Simulation results show that the hysteretic neural network can complete the prediction of the wind speed series,and the prediction performance is superior to that of the same type neural network.
Wind Speed Series Hysteretic Neural Network Prediction Training Samples
Wang Hongfei Xiu Chunbo Li Yanqing Cheng Yi Chen Yimei
School of Electrical Engineering and Automation,Tianjin polytechnic University,Tianjin 300387,China School of Electrical Engineering and Automation,Tianjin polytechnic University,Tianjin 300387,China; School of Mathematics and Physics,University of Science and Technology Beijing,Beijing 100083,China
国际会议
长沙
英文
762-765
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）