《计算机应用研究》|Application Research of Computers

地震前后基准站GPS数据异常提取算法

Detection of anomalies in GPS data before and after earthquakes

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作者 李南,孔祥增,林岭
机构 1.福建农林大学 计算机与信息学院,福州 350000;2.福建师范大学 数学与信息学院,福州 350000
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文章编号 1001-3695(2019)03-013-0706-05
DOI 10.19734/j.issn.1001-3695.2017.09.0931
摘要 目前对地震前兆异常的研究主要集中在“热”和“电”等方面,很少涉及基准站的GPS数据。然而已经有学者证明震中附近基准站的GPS时间序列坐标数据中也蕴涵着大地震的前兆信息。针对2001—2010年间美国本土发生的具有代表性的三个地震进行了研究,将Martingale理论运用于GPS数据处理,提出一种异常提取算法,进而对地震前后震中附近多个基准站的GPS数据进行分析。实验结果表明,算法能够有效地反映大地震前后GPS数据中异常的变化趋势,为使用GPS数据对大地震进行预报提供了更多可能。
关键词 地震;Martingale理论;异常提取
基金项目 国家自然科学基金青年基金资助项目(41601477)
福建省引导性项目(2015Y0054)
福建省自然科学基金资助项目(2016J01280)
本文URL http://www.arocmag.com/article/01-2019-03-013.html
英文标题 Detection of anomalies in GPS data before and after earthquakes
作者英文名 Li Nan, Kong Xiangzeng, Lin Ling
机构英文名 1.CollegeofComputer&InformationScience,FujianAgriculture&ForestryUniversity,Fuzhou350000,China;2.CollegeofMathematics&Information,FujianNormalUniversity,Fuzhou350000,China
英文摘要 Most research studies on forecasting of earthquakes focus on thermal or electrical aspects. Scholars have proved GPS time series also contains precursory information for large earthquakes. For the problems mentioned before, three typical earthquakes hit America from 2001 to 2010 were investigated by using GPS data of several GPS reference stations near the epicenters. This paper proposed an algorithm based on Martingale theory to detect the anomalies in GPS data. The experimental results show that the proposed algorithm can effectively reflect the change process in GPS data before and after large earthquakes, which offers more possibilities for earthquake forecast from GPS data.
英文关键词 earthquake; Martingale theory; anomaly detection
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收稿日期 2017/9/30
修回日期 2017/11/3
页码 706-710
中图分类号 TP301.6
文献标志码 A