EARTHQUAKE FORECASTING USING ARTIFICIAL NEURAL NETWORKS

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Pasari, S.^1¹  Bhatia, A.^1² 

[1] Dept. of Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India^2;Dept. of Mathematics, Birla Institute of Technology and Science, Pilani, Rajasthan, India^1

关键词: Earthquake Forecasting;    Neural Networks;    Multilayer Perceptron;    Recurrent Neural Networks;    LSTM Networks;   

DOI  :  10.5194/isprs-archives-XLII-5-823-2018

学科分类：地球科学(综合)

来源: Copernicus Publications

【 摘 要 】

Earthquake is one of the most devastating natural calamities that takes thousands of lives and leaves millions more homeless and deprives them of the basic necessities. Earthquake forecasting can minimize the death count and economic loss encountered by the affected region to a great extent. This study presents an earthquake forecasting system by using Artificial Neural Networks (ANN). Two different techniques are used with the first focusing on the accuracy evaluation of multilayer perceptron using different inputs and different set of hyper-parameters. The limitation of earthquake data in the first experiment led us to explore another technique, known as nowcasting of earthquakes. The nowcasting technique determines the current progression of earthquake cycle of higher magnitude earthquakes by taking into account the number of smaller earthquake events in the same region. To implement the nowcasting method, a Long Short Term Memory (LSTM) neural network architecture is considered because such networks are one of the most recent and promising developments in the time-series analysis. Results of different experiments are discussed along with their consequences.

【 授权许可】

CC BY