【摘要】 短期负荷预测中输入变量的选择直接关系到神经网络的预测性能。本文将自相关函数的概念应用于神经网络短期负荷预测中的输入变量集选择 ,对输入变量集的选择提出了一种比较科学系统的方法。通过采用FFT来实现对自相关函数的快速计算 ,增加了该方法的可操作性 ,并通过具体的实例验证了该方法的有效性。更多还原

【Abstract】 The input variables selection for short-term load forecasting is relevant to the performance of neural network forecasting. In this paper, by using the autocorrelation function on input variables sets selection for neural network short-term load forecasting, a systemic and scientific method for input variables sets selection is put forward. FFT is adopted to accomplish the speediness calculation, which enhances the maneuverability of this approach. A load forecasting example is given, whole result indicates that the method is effective.更多还原