| 基于EWT-ARMA的短期电离层TEC预测模型 |
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| 引用本文： | 鲁铁定,黄佳伟,鲁春阳,贺小星,钱文龙.基于EWT-ARMA的短期电离层TEC预测模型[J].大地测量与地球动力学,2021,41(4):331-335. |
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| 作者姓名： | 鲁铁定 黄佳伟 鲁春阳 贺小星 钱文龙 |
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| 作者单位： | 东华理工大学测绘工程学院,南昌市广兰大道418号,330013;河南城建学院测绘与城市空间信息学院,河南省平顶山市龙翔大道,467036;华东交通大学土木建筑学院,南昌市双港东大街808号,330013 |
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| 基金项目： | 江西省自然科学基金;国家自然科学基金;国家重点研发计划;江西省教育厅科学技术研究项目 |
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| 摘 要： | 针对电离层总电子含量（TEC）数据非线性、非平稳的特点，在自回归移动平均（ARMA）模型的基础上，结合经验小波变换（EWT），提出一种组合的短期电离层预测方法。采用IGS提供的电离层TEC格网数据进行实验，通过对比分析可知，相较于单一ARMA模型，本文组合模型在太阳活动低年和太阳活动高年5 d内的平均相对精度分别提高4.8%和2.8%，前1 d内组合模型的平均相对精度分别提高7%和6.1%。
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| 关 键 词： | 电离层总电子含量 ARMA模型 经验小波变换 预测模型 |
Short-Term Ionospheric TEC Prediction Model Based on EWT-ARMA |
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| LU Tieding,HUANG Jiawei,LU Chunyang,HE Xiaoxing,QIAN Wenlong.Short-Term Ionospheric TEC Prediction Model Based on EWT-ARMA[J].Journal of Geodesy and Geodynamics,2021,41(4):331-335. |
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| Authors: | LU Tieding HUANG Jiawei LU Chunyang HE Xiaoxing QIAN Wenlong |
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| Institution: | (Faculty of Geomatics,East China University of Technology,418 Guanglan Road,Nanchang 330013,China;School of Surveying and Urban Spatial Information,Henan University of Urban Construction,Longxiang Road,Pingdingshan 467036,China;School of Civil Engineering and Architecture,East China Jiaotong University,808 East-Shuanggang Street,Nanchang 330013,China) |
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| Abstract: | In view of the non-linear and non-stationary characteristics of the ionospheric total electron content(TEC)data,based on the auto-regressive moving average(ARMA)model prediction method and the empirical wavelet transform(EWT)method,we propose a combined short-term ionospheric prediction method.Using the ionospheric TEC grid data provided by IGS,the results show that,compared with the average relative accuracy of single ARMA model,the average relative accuracy of the combined model in low solar activity and high solar activity years is increased by 4.8%and 2.8%respectively,and the average relative accuracy of the combined model in the first day is increased by 7%and 6.1%. |
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| Keywords: | ionospheric total electron content ARMA model empirical wavelet transform prediction model |
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