A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China
Wang, S; Yu, L; Tang, L; Wang, SY
2011
Source PublicationENERGY
ISSN0360-5442
Volume36Issue:11Pages:13,6542-6554
AbstractDue to the distinct seasonal characteristics of hydropower, this study tries to propose a seasonal decomposition (SD) based least squares support vector regression (LSSVR) ensemble learning model for Chinese hydropower consumption forecasting. In the formulation of ensemble learning model, the original hydropower consumption series are first decomposed into trend cycle, seasonal factor and irregular component. Then the LSSVR with the radial basis function (RBF) kernel is used to predict the three different components independently. Finally, these prediction results of the three components are combined with another LSSVR to formulate an ensemble result for the original hydropower consumption series. In terms of error measurements and statistic test on the forecasting performance, the proposed approach outperforms all the other benchmark methods listed in this study in both level accuracy and directional accuracy. Experimental results reveal that the proposed SD-based LSSVR ensemble learning paradigm is a very promising approach for complex time series forecasting with seasonality. (C) 2011 Elsevier Ltd. All rights reserved.
KeywordHydropower Consumption Forecasting Lssvr Ensemble Learning Seasonal Decomposition
Subject AreaThermodynamics ; Energy & Fuels
Indexed BySCI
Language英语
WOS IDWOS:000297894500028
Citation statistics
Cited Times:60[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.casisd.cn/handle/190111/4255
Collection中国科学院科技政策与管理科学研究所(1985年6月-2015年12月)
Recommended Citation
GB/T 7714
Wang, S,Yu, L,Tang, L,et al. A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China[J]. ENERGY,2011,36(11):13,6542-6554.
APA Wang, S,Yu, L,Tang, L,&Wang, SY.(2011).A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China.ENERGY,36(11),13,6542-6554.
MLA Wang, S,et al."A novel seasonal decomposition based least squares support vector regression ensemble learning approach for hydropower consumption forecasting in China".ENERGY 36.11(2011):13,6542-6554.
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