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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