鲁东大学学报:自然科学版
魯東大學學報:自然科學版
로동대학학보:자연과학판
Ludong University Journal (Natural Science Edition)
2011年
4期
305-309,341
,共6页
赵烨华%张仲荣%石星宏%张恒
趙燁華%張仲榮%石星宏%張恆
조엽화%장중영%석성굉%장항
小波分析%非平稳时间序列%残差GM(11,)模型%ARIMA模型%组合预测
小波分析%非平穩時間序列%殘差GM(11,)模型%ARIMA模型%組閤預測
소파분석%비평은시간서렬%잔차GM(11,)모형%ARIMA모형%조합예측
wavelet analysis%non-stationary time series%residual GM ( 1,1 ) model%ARIMA model%combination forecast
提出了一种基于小波分析理论的残差GM(1,1)-ARIMA组合预测方法.利用小波多尺度分解和重构思想分解非平稳时间序列,并对信号进行拟合,再将各模型预测值叠加,得到原始时间序列的预测值.仿真实例验证了本文方法的有效性.
提齣瞭一種基于小波分析理論的殘差GM(1,1)-ARIMA組閤預測方法.利用小波多呎度分解和重構思想分解非平穩時間序列,併對信號進行擬閤,再將各模型預測值疊加,得到原始時間序列的預測值.倣真實例驗證瞭本文方法的有效性.
제출료일충기우소파분석이론적잔차GM(1,1)-ARIMA조합예측방법.이용소파다척도분해화중구사상분해비평은시간서렬,병대신호진행의합,재장각모형예측치첩가,득도원시시간서렬적예측치.방진실례험증료본문방법적유효성.
A residual GM(1,1)-ARIMA combination forecasting method based on wavelet analysis was proposed.Using the non-stationary time series decomposed by the wavelet multis-cale decomposition and reconstruction,the predicted value of the original time series was obtained by fitting the signals and superposing all model forecasting values.Experiment results showed that this method is reasonable and achieves good prediction accuracy.