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bestdimensionm
- 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
s23uan
- 本程序时基于混沌理论和ELMAN神经网络的短期负荷预测，能取得很好的预测效果，直接使用该程序就能实现电力短期负荷预测，同样使用于其他类型的时间序列预测-the procedures based on chaos theory and neural networks ELMAN short-term load forecasts, can be achieved very good results forecast, the direct use of the procedure we will
power
- 基于平移不变小波变换的电力时间序列预测，结合多层感知器（MLP）神经网络， 预测精度很好。-Electricity demand time-series forecasting program Based on shift-invariant wavelet transform features
RBF01
- 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
chapter15
- 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