Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148530
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. https://hdl.handle.net/10356/148530
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.
URI: https://hdl.handle.net/10356/148530
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SPMS Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Machine_learning_for_earthquake_prediction_Grace_Ang.pdf
  Restricted Access
432.77 kBAdobe PDFView/Open

Page view(s)

189
Updated on May 23, 2022

Download(s) 50

23
Updated on May 23, 2022

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.