Earthquake Prediction Using Expert Systems: A Systematic Mapping Study
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 systema...
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doaj-aa51dacc9a574873a19e15287d647f642020-11-25T02:20:10ZengMDPI AGSustainability2071-10502020-03-01126242010.3390/su12062420su12062420Earthquake Prediction Using Expert Systems: A Systematic Mapping StudyRabia Tehseen0Muhammad Shoaib Farooq1Adnan Abid2Department of Computer Science, University of Management and Technology, Lahore 54770, PakistanDepartment of Computer Science, University of Management and Technology, Lahore 54770, PakistanDepartment of Computer Science, University of Management and Technology, Lahore 54770, PakistanEarthquake 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.https://www.mdpi.com/2071-1050/12/6/2420expert systemssystematic mapping study (sms), earthquake predictionseismic dataearly-warning systems |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rabia Tehseen Muhammad Shoaib Farooq Adnan Abid |
spellingShingle |
Rabia Tehseen Muhammad Shoaib Farooq Adnan Abid Earthquake Prediction Using Expert Systems: A Systematic Mapping Study Sustainability expert systems systematic mapping study (sms), earthquake prediction seismic data early-warning systems |
author_facet |
Rabia Tehseen Muhammad Shoaib Farooq Adnan Abid |
author_sort |
Rabia Tehseen |
title |
Earthquake Prediction Using Expert Systems: A Systematic Mapping Study |
title_short |
Earthquake Prediction Using Expert Systems: A Systematic Mapping Study |
title_full |
Earthquake Prediction Using Expert Systems: A Systematic Mapping Study |
title_fullStr |
Earthquake Prediction Using Expert Systems: A Systematic Mapping Study |
title_full_unstemmed |
Earthquake Prediction Using Expert Systems: A Systematic Mapping Study |
title_sort |
earthquake prediction using expert systems: a systematic mapping study |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2020-03-01 |
description |
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. |
topic |
expert systems systematic mapping study (sms), earthquake prediction seismic data early-warning systems |
url |
https://www.mdpi.com/2071-1050/12/6/2420 |
work_keys_str_mv |
AT rabiatehseen earthquakepredictionusingexpertsystemsasystematicmappingstudy AT muhammadshoaibfarooq earthquakepredictionusingexpertsystemsasystematicmappingstudy AT adnanabid earthquakepredictionusingexpertsystemsasystematicmappingstudy |
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