Second, to improve the quality of short-term power load data, load data based on wavelet methods for detection of singularity analysis of the noise signal, and through the level and smoothing the data to eliminate the noise, the data provide a good basis for prediction.

Secondly in order to raise the short-term electric power burden data quality, carry on strange sex analysis examination noise signal to the burden data according to a method, and remove its noise through the level and smooth processing of the data, provide the good data foundation for the estimate.

Next for improves the short-term power load data quality, carries on the irregularity analysis examination noise signal based on the wavelet method to the load data, and eliminates its noise through the data level and smooth processing, provides the good data foundation for the forecast.

Followed by improving the quality of short-term electric power load data, methods to load data based on wavelet Singularity analysis of detection of noise signal and eliminate their noise level and smooth processing of the data, provide good data basis for forecasting.

Second, to improve the quality of short-term power load data, load data based on wavelet methods for detection of singularity analysis of the noise signal, and through the level and smoothing the data to eliminate the noise, the data provide a good basis for prediction.