Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

Rabia Tehseen, Muhammad Shoaib Farooq and Adnan Abid
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Rabia Tehseen: Department of Computer Science, University of Management and Technology, Lahore 54770, Pakistan
Muhammad Shoaib Farooq: Department of Computer Science, University of Management and Technology, Lahore 54770, Pakistan
Adnan Abid: Department of Computer Science, University of Management and Technology, Lahore 54770, Pakistan

Sustainability, 2020, vol. 12, issue 6, 1-32

Abstract: Earthquake is one of the most hazardous natural calamity. Many algorithms have been proposed for earthquake prediction using expert systems (ES). We aim to identify and compare methods, models, frameworks, and tools used to forecast earthquakes using different parameters. We have conducted a systematic mapping study based upon 70 systematically selected high quality peer reviewed research articles involving ES for earthquake prediction, published between January 2010 and January 2020.To the best of our knowledge, there is no recent study that provides a comprehensive survey of this research area. The analysis shows that most of the proposed models have attempted long term predictions about time, intensity, and location of future earthquakes. The article discusses different variants of rule-based, fuzzy, and machine learning based expert systems for earthquake prediction. Moreover, the discussion covers regional and global seismic data sets used, tools employed, to predict earth quake for different geographical regions. Bibliometric and meta-information based analysis has been performed by classifying the articles according to research type, empirical type, approach, target area, and system specific parameters. Lastly, it also presents a taxonomy of earthquake prediction approaches, and research evolution during the last decade.

Keywords: Expert systems; Systematic Mapping Study (SMS), earthquake prediction; seismic data; Early-warning systems (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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