It is important to select input variables when the neural network forecasting model is proposed. In this pa-per, by using the autocorrelation function on input variables sets selection for neural network forecasting m...It is important to select input variables when the neural network forecasting model is proposed. In this pa-per, by using the autocorrelation function on input variables sets selection for neural network forecasting model, asystemic and scientific method for input variables sets selection is put forward. FFT is adopted to accomplish thespeediness calculation, which enhances the maneuverability of this approach. A forecasting example is given, whoseresult indicates that the method is effective.展开更多
文摘It is important to select input variables when the neural network forecasting model is proposed. In this pa-per, by using the autocorrelation function on input variables sets selection for neural network forecasting model, asystemic and scientific method for input variables sets selection is put forward. FFT is adopted to accomplish thespeediness calculation, which enhances the maneuverability of this approach. A forecasting example is given, whoseresult indicates that the method is effective.
