| 深度学习预测GPS时间序列在探索门源MS6.4地震前兆中的应用 |
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| 引用本文： | 陈善鹏,尹 玲,梁诗明,胡向阳,余小燕.深度学习预测GPS时间序列在探索门源MS6.4地震前兆中的应用[J].大地测量与地球动力学,2020,40(12):1248-1253. |
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| 作者姓名： | 陈善鹏 尹 玲 梁诗明 胡向阳 余小燕 |
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| 摘 要： | 以2016-01-21门源MS6.4地震为例，提出用深度学习预测的GPS时间序列研究地震前兆。用震中附近门源台（QHME）、民乐台（GSML）及古浪台（GSGL）无震时的GPS时间序列训练LSTM神经网络，得到高精度的GPS时间序列预测模型，再分别对该地区无震时和地震前一段时间的GPS时间序列进行回溯性预测。对比预测时间序列与真实时间序列发现，震前2条时间序列大部分的相似性指标比无震时低，说明震前预测时间序列与真实时间序列差异明显，同时考虑震前时间序列的趋势异常，认为出现了异常时段；3个台站分别在E、N、U方向出现多个异常日期，且不同台站具有相同的异常日期，说明探索到了地震前兆。
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| 关 键 词： | 门源地震 GPS时间序列 LSTM神经网络 前兆异常 |
Application of Deep Learning to Predict GPS Time Series in Exploring Precursors of Menyuan MS6.4 Earthquake |
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| CHEN Shanpeng,YIN Ling,LIANG Shiming,HU Xiangyang,YU Xiaoyan.Application of Deep Learning to Predict GPS Time Series in Exploring Precursors of Menyuan MS6.4 Earthquake[J].Journal of Geodesy and Geodynamics,2020,40(12):1248-1253. |
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| Authors: | CHEN Shanpeng YIN Ling LIANG Shiming HU Xiangyang YU Xiaoyan |
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| Abstract: | This paper proposes to use GPS time series predicted by deep learning to study earthquake precursors, taking the earthquake of MS6.4 in Menyuan, on January 21, 2016 as an example. To obtain a high-precision GPS time series prediction model, the LSTM neural network is trained with GPS time series of historical non-seismic time series of Menyuan station(QHME), Minle station(GSML) and Gulang station(GSGL) near the epicenter, and then the GPS time series of non-seismic time series and the period of time before the earthquake in the region are predicted retroactively. Through comparative analysis of the predicted time series and the real time series, we find that most indexes of the similarity between the two time series before the earthquake are lower than those of the time series without the earthquake, which indicates that the predicted time series before the earthquake is obviously different from the real time series. Meanwhile, considering the trend anomaly of the time series before the earthquake, the abnormal time period is considered to have occurred. The three stations have multiple abnormal dates in E,N and U directions, and different stations have the same abnormal date. The discovery of abnormal periods and abnormal dates indicates that earthquake precursors have been explored. |
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| Keywords: | Menyuan earthquake GPS time series LSTM neural network precursor anomaly |
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