Original scientific paper
https://doi.org/10.17535/crorr.2016.0011
Earthquake magnitude prediction based on artificial neural networks: A survey
Emilio Florido
; Division of Computer Science, Pablo de Olavide University, ES-41013 Seville, Spain
José L. Aznarte
orcid.org/0000-0002-1636-244X
; Department of Artifi cial Intelligence, Universidad Nacional de Educación a Distancia-UNED, Spain
Antonio Morales-Esteban
orcid.org/0000-0002-3358-3690
; Department of Building Structures and Geotechnical Engineering, University of Seville, Spain
Francisco Martínez-Álvarez
; Division of Computer Science, Pablo de Olavide University, ES-41013 Seville, Spain
Abstract
The occurrence of earthquakes has been studied from many aspects. Apparently, earthquakes occur without warning and can devastate entire cities in just a few seconds, causing numerous casualties and huge economic loss. Great effort has been directed towards being able to predict these natural disasters, and taking precautionary measures. However, simultaneously predicting when, where and the magnitude of the next earthquake, within a limited region and time, seems an almost impossible task. Techniques from the field of data mining are providing new and important information to researchers. This article reviews the use of artificial neural networks for earthquake prediction in response to the increasing amount of recently published works and presenting claims of being effective. Based on an analysis and discussion of recent results, data mining practitioners are encouraged to apply their own techniques in this emerging field of research.
Keywords
data mining; prediction; earthquake; time series
Hrčak ID:
174130
URI
Publication date:
30.12.2016.
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