在用混沌理论和神经网络进行短期负荷预测时，神经网络的输入的选择至关重要，该程序用matlabl实现了基于混沌时间序列的嵌入维数的选择-using chaos theory and neural networks for short-term load forecasts, the neural network is essential to choose an input, The procedure used matlabl achieved a chaotic time series bas

基于时间序列相空间重构和RBF神经网络的短时交通流量预测学习方法-Based on time series phase space reconstruction and RBF neural network method of short-term traffic flow prediction study

基于SVM神经网络的信息化时间序列回归预测问题-Based on the SVM neural network informationization time series regression prediction problem

source code of time series forecasting for various models such as neural network all these source code on matalb