用此程序可以实现小波变换，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-This process can be achieved with wavelet transform, chaos theory and neural networks with short-term load forecasting, neural network is essential to choose the input

随着新的数学工具小波分析的实用化为基于NN负荷预测模型性能的改善提供了理论依据对于电力系统负荷非线性时间序列的辨识在预测方法研究中应给予重视在本文所用的基于小波原理和NN融合的预测原理是具有强的非线性-With the new mathematical tools of wavelet analysis into practical load forecasting model based on the performance of NN provides a theoretical basis

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-In chaos theory and neural networks with short-term load forecasting, neural network is essential to choose the input, the program implemented with matlabl chaotic time series based o

一个多输入多输出小波网络的源程序，用matlab编写，能够实现对时间序列数据的训练预测-A multi-input multi-output wavelet network' s source code, written with matlab, can be achieved on the training time series data forecasting

Elman神经网络的数据预测—电力负荷预测模型研究-Data Elman neural network prediction- the power load forecasting model study