A New Algorithm for Earthquake Prediction Using Machine Learning Methods
- 1 Department of Computer Science, College of Computer Sciences and Maths, University of Kufa, Iraq
- 2 Department of Computer Information Systems, College of Computer Sciences and Information Technology, University of Basrah, Basrah, Iraq
- 3 Department of Technology Engineering College of Information Technology, Imam Ja'afar Al-Sadiq University, Baghdad, Iraq
Abstract
Seismic tremors are among the foremost perilous normal fiascos individuals confront due to their event without earlier caution and their effect on their lives and properties. In expansion, to consider future disaster prevention measures for major earthquakes, it is necessary to predict earthquakes using Neural Networks (NN). A machine learning technique has developed a technology to predict earthquakes from ground controller data by measuring ground vibration and transmitting data by a sensor network. Devices to process this data and record it in a catalog of seismic data from 1900-2019 for Iraq and neighboring regions, then divide this data into 80% training data and 20% test data. It gave better results than other prediction algorithms, where the NN model performs better Seismic prediction than other machine learning methods.
DOI: https://doi.org/10.3844/jcssp.2024.150.156
Copyright: © 2024 Nada Badr Jarah, Abbas Hanon Hassin Alasadi and Kadhim Mahdi Hashim. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Earthquakes
- Neural Networks
- Machine Learning
- Prediction
- Earthquakes Data