Abstract
Acoustic and electromagnetics to artificial intelligence (AETA) is a system used to predict seismic events through monitoring of electromagnetic and geoacoustic signals. It is widely deployed in the Sichuan–Yunnan region (22° N–34° N, 98° E–107° E) of China. Generally, the electromagnetic signals of AETA stations near the epicenter have abnormal disturbances before an earthquake. When a significant decrease or increase in the signal is observed, it is difficult to quantify this change using only visual observation and confirm that it is related to an upcoming large earthquake. Considering that the AETA data comprise a typical time series, current work has analyzed the anomalism of AETA electromagnetic signals using the long short-term memory (LSTM) autoencoder method to prove that the electromagnetic anomaly of the AETA station can be regarded as an earthquake precursor. The results show that there are 2–4% anomalous points and some outliers exceeding 0.7 (after normalization) in the AETA stations within 200 km of the epicenter of the Jiuzaigou earthquake (M. 7.0) and the Yibin earthquake (M. 6.0) half a month before the earthquakes. Therefore, the AETA electromagnetic disturbance signal can be used as an earthquake precursor and for further earthquake prediction.
Funder
Shenzhen science & technology
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献