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 investigate 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 network (TCN). From the computational
results, we confirm that the TCN captures the relation between SA and earthquakes with magnitudes from 4.0 to 4.9. We
also find that the TCN achieves
better fitting and prediction performance compared with previous work.
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