Earthquake prediction technique: a comparative study

Jarah N.B.; Hassin Alasadi A.H.; Hashim K.M.

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Earthquake prediction technique: a comparative study

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Earthquakes are one of the most dangerous natural disasters facing humans because of their occurrence without warning and their impact on their lives and property. In addition, predicting seismic movement is one of the main research topics in seismic disaster prevention. In geological studies, scientists can predict and know the locations of earthquakes in the long term. Therefore, about 80 of the major global earthquakes lie along the Pacific Ring belt, known as the Ring of Fire. Machine learning methods have also been used for short-term earthquake prediction, and studies have applied the random forest method to determine the factors that precede earthquakes. The machine learning method was based on various decision trees, each of which predicted the time to the nearest oscillation. The third group of scientists used the hybrid prediction method, which combines machine learning and geological studies. This research deals with a review of most of the geological studies and machine learning techniques applied to earthquake data sets, which showed a total lack of prediction of potential earthquakes through one approach, so studies designed by geologists were combined with machine learning. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

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来源
《IAES International Journal of Artificial Intelligence》 |2023年第3期|1026-1032|共7页
作者
Jarah N.B.; Hassin Alasadi A.H.; Hashim K.M.;
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作者单位

Statistics Department, General Specialty: Computer Science, College of Management and Economics, University of Basrah;

Information Systems Department, College of Computer Sciences and Information Technology, University of Basrah;

Computer Technology Engineering Department, College of Information Technology, Imam Ja'afar Al-Sadiq University;

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原文格式 PDF
正文语种英语
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关键词
Earthquakes; Geology science; Hybrid; Machine learning; Prediction;

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Earthquake prediction technique: a comparative study

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