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
发表期刊ENERGY
关键词Hydropower Consumption Forecasting Lssvr Ensemble Learning Seasonal Decomposition
摘要Due 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.
2011
卷号36期号:11页码:13,6542-6554
ISSN0360-5442
学科领域Thermodynamics ; Energy & Fuels
收录类别SCI
语种英语
WOS记录号WOS:000297894500028
引用统计
被引频次:69[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.casisd.cn/handle/190111/4255
专题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)
推荐引用方式
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.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
A novel seasonal dec(913KB) 开放获取--浏览
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Wang, S]的文章
[Yu, L]的文章
[Tang, L]的文章
百度学术
百度学术中相似的文章
[Wang, S]的文章
[Yu, L]的文章
[Tang, L]的文章
必应学术
必应学术中相似的文章
[Wang, S]的文章
[Yu, L]的文章
[Tang, L]的文章
相关权益政策
暂无数据
收藏/分享
文件名: A novel seasonal decomposition based least squares support vector regression.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。