Academic Journal of Computing & Information Science, 2023, 6(12); doi: 10.25236/AJCIS.2023.061210.
Zhijun Li1, Gege Jin2, Hongmei Yin3, Chen Chen4, Jiyong Hua1
1Yangzhou University, Yangzhou, China
2Yangzhou Technician Branch, Jiangsu United Vocational and Technical College, Yangzhou, China
3Yangzhou Customs, Yangzhou, China
4Jiangsu College of Tourism, Yangzhou, China
Earthquake prediction is a difficult task. Constrained within a certain spatiotemporal range, earthquakes are only a probability event. In a large area, predicting earthquakes based on geographical events that have already occurred is reliable. Predicting the duration of aftershocks under the condition that a major earthquake has already occurred is the research content of this article. Extract 6 features from seismic phase data to predict the aftershock period. We constructed a convolutional neural network model, sorted out 855 data from 1351 data, and trained the network. The accuracy of training verification reaches 90%, and the accuracy of testing reaches 100%. After further refinement, this model can be used to predict the duration of aftershocks in earthquakes. Provide data guidance for earthquake rescue.
Convolution Neural Network; Aftershock Predict; Earthquake Predict
Zhijun Li, Gege Jin, Hongmei Yin, Chen Chen, Jiyong Hua. Aftershock predict based on convolution neural networks. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 12: 90-96. https://doi.org/10.25236/AJCIS.2023.061210.
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