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NN and SVR implementation for Earthquake prediction

COGS118B 2022FA

Group members:

Andrina / Xiaoxuan Zhang, Alexander Huynh, Victorionna Tran, Nicolas Schaefer

Presentation video:

https://youtu.be/PW_n3AHvA10

Presentation slides:

https://docs.google.com/presentation/d/1pluFLWJl29U45WkxpcH_bu0kdAwriR8w6QYsswkTnms/edit

Background

Everything happening with nature has tremendous impacts on human beings. Earthquakes and natural disasters may take away countless people's lives. Earthquake prediction has been around for a while but has yielded no real success and our group wants to work on this topic too. At the very beginning of the project, our group wanted to work on the time series data of earthquake waveforms, trying to predict how the wave may traverse to predict the earthquake's severity. However, the data we could find online was not very ideal to predict the waveform. Fortunately, we are able to find a dataset that contains the Data, Time, Latitude, Longitude, Magnitude, Depth, and Region of the earthquake. The core components made us possible to work on the earthquake prediction model.

Research Question

Can we accurately predict the magnitude and depth of an earthquake happening, given the time and location (latitude and longitude) it will occur? We would like to know the relationship between the time and location of earthquakes The general prediction and patterns on magnitude and depth of earthquakes may also apply to the decision of future urban planning and architect designs With the consideration of these components, the government may design different focuses based on different locations to decrease the effect of earthquakes. With further influence, this workʼs importance pertains to the livelihood of people.

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