| Prediction of Length-of-day Using Gaussian Process Regression | |
Lei, Yu1,2; Guo, Min3; Cai, Hongbing1; Hu, Dandan3 ; Zhao, Danning1,2
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| 2015-05-01 | |
| 发表期刊 | JOURNAL OF NAVIGATION
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| 卷号 | 68期号:3页码:563-575 |
| 摘要 | The predictions of Length-Of-Day (LOD) are studied by means of Gaussian Process Regression (GPR). The EOP C04 time-series with daily values from the International Earth Rotation and Reference Systems Service (IERS) serve as the data basis. Firstly, well known effects that can be described by functional models, for example effects of the solid Earth and ocean tides or seasonal atmospheric variations, are removed a priori from the C04 time-series. Only the differences between the modelled and actual LOD, i.e. the irregular and quasi-periodic variations, are employed for training and prediction. Different input patterns are discussed and compared so as to optimise the GPR model. The optimal patterns have been found in terms of the prediction accuracy and efficiency, which conduct the multi-step ahead predictions utilising the formerly predicted values as inputs. Finally, the results of the predictions are analysed and compared with those obtained by other prediction methods. It is shown that the accuracy of the predictions are comparable with that of other prediction methods. The developed method is easy to use. |
| 文章类型 | Article |
| 关键词 | Length-of-day Lod) Prediction Gaussian Process Regression (Gpr) |
| WOS标题词 | Science & Technology ; Technology ; Physical Sciences |
| DOI | 10.1017/S0373463314000927 |
| 收录类别 | SCI |
| 关键词[WOS] | LEAST-SQUARES ; EARTH ; PARAMETERS |
| 语种 | 英语 |
| WOS研究方向 | Engineering ; Oceanography |
| WOS类目 | Engineering, Marine ; Oceanography |
| WOS记录号 | WOS:000352011100010 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/24125 |
| 专题 | 研究生部 |
| 作者单位 | 1.Chinese Acad Sci, Natl Time Serv Ctr, Beijing 100864, Peoples R China 2.Univ Chinese Acad Sci, Jinan, Peoples R China 3.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Beijing 100864, Peoples R China |
| 推荐引用方式 GB/T 7714 | Lei, Yu,Guo, Min,Cai, Hongbing,et al. Prediction of Length-of-day Using Gaussian Process Regression[J]. JOURNAL OF NAVIGATION,2015,68(3):563-575. |
| APA | Lei, Yu,Guo, Min,Cai, Hongbing,Hu, Dandan,&Zhao, Danning.(2015).Prediction of Length-of-day Using Gaussian Process Regression.JOURNAL OF NAVIGATION,68(3),563-575. |
| MLA | Lei, Yu,et al."Prediction of Length-of-day Using Gaussian Process Regression".JOURNAL OF NAVIGATION 68.3(2015):563-575. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Prediction of Length（545KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY | 请求全文 | |
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