Earthquake Prediction: A MLP & SVM Comparison

Bachelor thesis (2022)

Authors

D.A. van den Akker Electrical Engineering, Mathematics and Computer Science

Contributors

E. Isufi (supervisor 1)
Maosheng Yang (supervisor 1)
M. Sabbaqi (supervisor 1)
D.M.J. Tax Pattern Recognition and Bioinformatics - EEMCS (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Daniel van den Akker
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Published Date

28-01-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Multi-Layer Perceptron and Support Vector Machine have both been widely used in machine learning. In this research paper, these models have been applied to binary classification on an individual time series basis. The goal was to see whether they can predict earthquakes, using earthquakes measured at specific stations across New Zealand. As it turns out, both models serve as satisfactory classifiers. However, their performances are dependent on the stations the data was accumulated from.