张志玮, 李子扬, 朱小华, 李传荣. 2016: 基于电磁探测数据的时序分析模型研究. 地震学报, 38(3): 408-416. DOI: 10.11939/jass.2016.03.008
引用本文: 张志玮, 李子扬, 朱小华, 李传荣. 2016: 基于电磁探测数据的时序分析模型研究. 地震学报, 38(3): 408-416. DOI: 10.11939/jass.2016.03.008
Zhang Zhiwei, Li Ziyang, Zhu Xiaohua, Li Chuanrong. 2016: Time series analysis model based on electromagnetic detection data. Acta Seismologica Sinica, 38(3): 408-416. DOI: 10.11939/jass.2016.03.008
Citation: Zhang Zhiwei, Li Ziyang, Zhu Xiaohua, Li Chuanrong. 2016: Time series analysis model based on electromagnetic detection data. Acta Seismologica Sinica, 38(3): 408-416. DOI: 10.11939/jass.2016.03.008

基于电磁探测数据的时序分析模型研究

Time series analysis model based on electromagnetic detection data

  • 摘要: 针对电磁探测数据交叉检验时对不同卫星探测数据的时间匹配需求,本文基于DEMETER卫星时序探测数据,分析了国际参考电离层(IRI)模型模拟电子浓度(Ne)数据在不同纬度区域的误差分布特征; 同时,基于自回归移动平均(ARIMA)模型构建了Ne数据时序预测模型. 在此基础上,分析比较IRI模型与ARIMA模型在Ne数据时序预测中的优缺点,结果表明: ARIMA模型模拟预测Ne数据时间序列的相对误差在短期内较低(小于10%),且随着预测时间的增长而增大; 而IRI模型模拟预测Ne数据时间序列的相对误差不会随着预测时间的增长而增大,且在高纬度地区的预测相对误差比在中低纬度地区低.

     

    Abstract: Due to the demand for the time matching of different satellites data during cross-calibration of electromagnetic detection data, this paper analyzes the error distribution features of electron density (Ne) simulated based on the international reference ionosphere (IRI) model at different latitudes by using the time series data of DEMETER satellite. At the same time, based on the autoregre-ssive integrated moving average (ARIMA) model, the Ne data time series forecasting model is constructed. By comparing with the IRI model, the advantages and disadvantages of ARIMA model are analyzed in simulated prediction of the Ne time series data. The results show that the relative error of ARIMA forecasting model is small in the short-time (the relative error less than 10%), however, becomes greater in the long time. Whereas, the relative error of IRI model in simulated prediction of Ne time series data does not become larger in the long time, and the relative error at high latitudes is lower than that at low and moderate latitudes.

     

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