Importance of Machine Learning and Deep Learning Algorithms in Earthquake Prediction: A Review
Güneş Gürsoy, Asaf Varol, Ahad Nasab
Abstract
Earthquakes are the leading natural disasters that have caused loss of life and property since the formation of the world. Machine learning and deep learning are frequently used in studies for earthquake prediction. This article consists of a compilation of studies using machine learning and deep learning algorithms. In the article, studies on topics such as earthquake magnitude estimation, signal discrimination, electron density estimations in the ionosphere, examination of radon gas anomalies using machine learning and deep learning algorithms are included. The studies in this paper show that Deep Learning algorithms are used more frequently in earthquake forecasting. It is expected that Deep Learning will provide more successful results in future studies due to its ability to work with larger data sets compared to Machine Learning and its ability to improve itself from errors.