Author:
Wang Chenyang,Li Chaorun,Yong Shanshan,Wang Xin’an,Yang Chao
Abstract
The Key Laboratory of Integrated Microsystems (IMS) of Peking University Shenzhen Graduate School has deployed a self-developed acoustic and electromagnetics to artificial intelligence (AETA) system on a large scale and at a high density in China to comprehensively monitor and collect the precursor anomaly signals that occur before earthquakes for seismic prediction. This paper constructs several classic time series and non-time series prediction models for comparison and analysis in order to find the most suitable earthquake-prediction model among these models. The long short-term memory (LSTM) neural network, which gains the best results in earthquake prediction based on AETA data extracted from the precursor anomaly signals, is selected for real-earthquake prediction for 16 consecutive weeks.
Funder
Youth Innovation Talent Project of Guangdong Province Universities
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
2 articles.
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