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	Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine
	Yuan, Xiaohui; Tan, Qingxiong; Lei, Xiaohui*; Yuan, Yanbin; Wu, Xiaotao
刊名	Energy
	2017
卷号	129页码:122-137
关键词	Wind power prediction Autoregressive fractionally integrated moving average Least square support vector machine Autocorrelation function Long memory characteristics
ISSN号	0360-5442
DOI	10.1016/j.energy.2017.04.094
URL标识	查看原文
WOS记录号	WOS:000403987900011;EI:20171703612413
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/3368567
专题	武汉理工大学
作者单位	1.[Yuan, Xiaohui 2.Tan, Qingxiong 3.Wu, Xiaotao] Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China.
推荐引用方式 GB/T 7714	Yuan, Xiaohui,Tan, Qingxiong,Lei, Xiaohui*,et al. Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine[J]. Energy,2017,129:122-137.
APA	Yuan, Xiaohui,Tan, Qingxiong,Lei, Xiaohui*,Yuan, Yanbin,&Wu, Xiaotao.(2017).Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine.Energy,129,122-137.
MLA	Yuan, Xiaohui,et al."Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine".Energy 129(2017):122-137.

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