Applications of machine learning for earthquake prediction: A review

Abstract

Earthquake is one of most devastating natural disasters. The earthquake occurrences prediction, help reduced magnitude of destruction minimized.for Predicting an earthquake's time, magnitude,depth and location of the earthquake, a variety of techniques have been suggested, such as statistical and mathematical analysis, and a signal investigation of precursors,due an ostensibly dynamic character of seismic, they usually do not produce excellent results.The capacity of Artificial Intelligence (AI) to detect hidden patterns of data is well-known in the earthquake forecasting case.This paper provides overview of the different techniques and a comparison of their results.In AI-based approaches were utilized to forecast earthquakes using a variety of academic datasets. These researches used a variety of machine learning approaches that examines the contributions made of the prediction of earthquakes based on AI approaches to date. Furthermore, its goal to make choosing relevant earthquake prediction system. These studies review at ANN-based approaches, clustering techniques, and machine learning techniques for earthquake prediction.