WIND SPEED PREDICTION BASED ON WAVELET ANALYSIS AND TIME SERIES METHOD

被引:0
|
作者
Zhao, Zheng [1 ]
Wang, Xiao-Liang [1 ]
Zhang, Ya-Gang [2 ]
Gou, Hai-Zhi [1 ]
Yang, Fan [1 ]
机构
[1] North China Elect Power Univ, Dept Automat, Baoding 071003, Peoples R China
[2] North China Elect Power Univ, Dept Math, Baoding 071003, Peoples R China
来源
2017 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR) | 2017年
关键词
Wind speed prediction; Wavelet transform; Time-series; Nonlinear least square;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In order to improve the accuracy of wind speed prediction, the paper proposed a brand new prediction model, called the nonlinear least squares autoregressive moving average model, which based on the wavelet decomposition and reconstruction. Firstly, this model introduces the wavelet transform, which decomposes the original non-stationary wind speed sequence into a relatively stable sequence; Then it gets established the nonlinear least squares autoregressive moving average model and makes single step prediction for each sequence decomposed by the wavelet, during the prediction update the value of history sequence constantly; Finally, for the sake of the outcome of the original wind speed series, it sums up the prediction result of each layer decomposed by the wavelet. The results of actual calculation show that the time series forecasting method based on wavelet decomposition is better than the traditional method, and has higher prediction precision in wind forecasting.
引用
收藏
页码:23 / 27
页数:5
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