Seismic Reflection Analysis of AETA Electromagnetic Signals
APPLIED SCIENCES-BASEL(2021)
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 degrees N-34 degrees N, 98 degrees E-107 degrees 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.
MoreTranslated text
Key words
AETA,anomaly detection,LSTM autoencoder,earthquake precursor,unsupervised learning
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined