LSTM-based Groundwater Level Prediction and Anomaly Analysis of Earthquake Precursors
Due to the influence of earthquakes,groundwater levels can undergo abnormal changes.The prediction study of water level change has important theoretical and practical significance for the analysis of possible earthquake precursors and the mitigation of secondary disasters.In this study,the earthquake selected occurred on April 13,2015,at 10:28 a.m.,in Jianshui County,Honghe Hani and Yi Autonomous Prefecture,Yunnan Province.By obtaining groundwater level data from observation wells in the vicinity of the earthquake,the dataset is divided based on the theoretical concepts of earthquake active and non-active periods.Subsequently,an LSTM model is employed for training.The differences between the predicted values and the actual values are observed.Experimental results indicate that the model can identify abnormal changes in groundwater levels caused by earthquakes,providing valuable insights into studying groundwater level anomalies as earthquake precursors.
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