【摘要】 提出一种将混沌时间序列和神经网络相结合的短期负荷预测方法,利用混沌理论重构相空间的吸引子,然后用BP神经网络来拟合空间吸引子的演化,同时利用空间欧氏距离来选取神经网络的输入样本,实例预测结果表明所提出方法的有效性和可行性.更多还原

【Abstract】 A method of short-term load forecasting based on chaotic time series and neural networks is presented in this paper.Firstly,attractors in phase spaces using chaotic theory is reconstructed.Secondly,the attractor’s evolvement using BP neural networks is made,and the neural network’s input data using Euclid distance is selected.The result analysis of the practical examples show that the proposed method is effective and feasible.更多还原