In this project, I develop machine learning models to seperate earthquake signals from nuclear explosions. Both earthquakes and nuclear explosions generate seismic waves that can be detected thousands of kilometers away. However, it is not always an easy task to separate them from each other. Although seismologists have developed methods, it is sometimes very challenging. For example, a recent 3.4 magnitude quake from North Korea was interpreted as 'suspected explosion' but later identified as natural. More details can be found here : http://www.independent.ie/world-news/asia-pacific/small-north-korea-earthquake-likely-natural-not-caused-by-nuclear-test-say-experts-36161584.html
The primary objective is to develop machine learning models to separate natural earthquakes from nuclear explosions.
For anything about the implementations, please feel free to write me an email :
Sabber Ahamed msahamed@memphis.edu Center For Earthquake Research and Information (CERI) The University of Memphis 3890 Central Ave Memphis, TN 38152, USA
This project requires Python 2.7 or 3. I have Used python 3.0. The following Python libraries are also required:
Datasets are not included to this project due to size. Please email me msahamed@memphis.edu if you need the datasets.
Bug reports, comments, and suggestions are always welcome. The best the channel is to create an issue on the Issue Tracker here at the repository : https://github.com/msahamed/classify-earthquakes-nuclear-explosion
This program is free software: you can redistribute it and modify it under the terms of the MIT.