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Investigation of Relation between Solar Activity and Earthquakes with Deep Learning Method
Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
Mazda Motor Company, Hiroshima, Japan
School of Information and Data Sciences, Nagasaki University, Nagasaki, Japan
Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
- 1 Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
- 2 Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
- 3 Mazda Motor Company, Hiroshima, Japan
- 4 School of Information and Data Sciences, Nagasaki University, Nagasaki, Japan
- 5 Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
International Journal of Geosciences·Volume 12 (2021)·Pages 704–713·Published 6 August 2021·DOI10.4236/ijg.2021.128040
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Abstract
Solar activity (SA) has been hypothesized to be a trigger of earthquakes, although it is not as intuitively associated as other potential triggers such as tidal stress, rainfall, and the building of artificial water reservoirs. Here, we in ves tigate the relation between SA and global earthquake numbers (GEN) by using a deep learning method to test the hypothesis. We use the daily data of GEN and SA (1996/01/01 - 2019/12/31) to construct a temporal convolution netw ork ( TCN). From the computational results, we confirm that the TCN captures th e relation between SA and earthquakes with magnitudes from 4.0 to 4.9. We als o find that the TCN achieves better fitting and prediction performance compar ed with previous work .
KeywordsDeep LearningEarthquakesPredictionSolar ActivitiesTemporal Convolution Network
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