Real-time rapid prediction of variations of Earth's rotational rate
文献类型：期刊论文
| 作者 | Wang QiJie2; Liao DeChun2; Zhou YongHong2 |
| 刊名 | CHINESE SCIENCE BULLETIN
 |
| 出版日期 | 2008 |
| 卷号 | 53期号:7页码:969 |
| 关键词 | PARAMETERS LENGTH real-time prediction variation of Earth's rotational rate atmospheric angular momentum artificial neural networks |
| ISSN号 | 1001-6538 |
| 英文摘要 | Real-time rapid prediction of variations of the Earth's rotational rate is of great scientific and practical importance. However, due to the complicated time-variable characteristics of variations of the Earth's rotational rate (i.e., length of day, LOD), it is usually difficult to obtain satisfactory predictions by conventional linear time series analysis methods. This study employs the nonlinear artificial neural networks (ANN) to predict the LOD variations. The topology of the ANN model is determined by minimizing the root mean square errors (RMSE) of the predictions. Considering the close relationships between the LOD variations and the atmospheric circulation movement, the operational prediction series of axial atmospheric angular momentum (AAM) is incorporated into the ANN model as an additional input in the real-time rapid prediction of LOD variations with 1-5 days ahead. The results show that the LOD prediction is significantly improved after introducing the operational prediction series of AAM into the ANN model. |
| 语种 | 英语 |
| 源URL | [http://ir.bao.ac.cn/handle/114a11/56792]  |
| 专题 | 中国科学院国家天文台 |
| 作者单位 | 1.中国科学院大学 2.中国科学院国家天文台 3.Cent S University, Sch Info Phys & Geomat Engn, Changsha 410083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang QiJie,Liao DeChun,Zhou YongHong. Real-time rapid prediction of variations of Earth's rotational rate[J]. CHINESE SCIENCE BULLETIN,2008,53(7):969. |
| APA | Wang QiJie,Liao DeChun,&Zhou YongHong.(2008).Real-time rapid prediction of variations of Earth's rotational rate.CHINESE SCIENCE BULLETIN,53(7),969. |
| MLA | Wang QiJie,et al."Real-time rapid prediction of variations of Earth's rotational rate".CHINESE SCIENCE BULLETIN 53.7(2008):969. |
入库方式： OAI收割
来源：国家天文台
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