Earthquake Risk Prediction With Artificial Intelligence Methods

Abstract

Earthquakes are one of the most difficult natural phenomena in human history to predict. Today, despite very advanced technologies, earthquake predictions still have not been conclusive. It is especially known that the trilogy of location, time, and magnitude is quite difficult to predict at the same time. In order to discover this powerful natural phenomenon, scientists are trying to collect and make sense of the parameters affecting the earthquake and the earthquake results. In general, their goal is to determine the characteristics that have an impact on earthquakes, to perform classifications thanks to various artificial intelligence algorithms, and to predict future earthquakes. The aim of this study is to compile, examine, and analyze earthquake risk prediction researches or applications carried out using artificial intelligence methods. The studies obtained as a result of the literature review were grouped according to the metrics used, data sets, features, and models used and evaluated according to the success rates obtained.