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Title: Machine learning for earthquake prediction
Authors: Ang, Grace Li Ling
Keywords: Science::Geology::Volcanoes and earthquakes
Science::Mathematics::Applied mathematics::Simulation and modeling
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Ang, G. L. L. (2021). Machine learning for earthquake prediction. Final Year Project (FYP), Nanyang Technological University, Singapore.
Abstract: Earthquake prediction for the region of Sendai, Japan was carried out in this study by using 7 seismic features as inputs to an artificial neural network. The seismic indicators are selected based on well-known seismological and geophysical facts and are able to represent the seismic state of a specific region. Prediction results were evaluated using 5 measures: Sn, Sp, P1, P0 and Accuracy. Overall, the prediction accuracy is not satisfactory, suggesting the use of a deeper learning neural network.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)

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