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Reseach Article

Study on Techniques of Earthquake Prediction

by G.Preethi, B.Santhi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 29 - Number 4
Year of Publication: 2011
Authors: G.Preethi, B.Santhi
10.5120/3549-4867

G.Preethi, B.Santhi . Study on Techniques of Earthquake Prediction. International Journal of Computer Applications. 29, 4 ( September 2011), 55-58. DOI=10.5120/3549-4867

@article{ 10.5120/3549-4867,
author = { G.Preethi, B.Santhi },
title = { Study on Techniques of Earthquake Prediction },
journal = { International Journal of Computer Applications },
issue_date = { September 2011 },
volume = { 29 },
number = { 4 },
month = { September },
year = { 2011 },
issn = { 0975-8887 },
pages = { 55-58 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume29/number4/3549-4867/ },
doi = { 10.5120/3549-4867 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:15:42.110398+05:30
%A G.Preethi
%A B.Santhi
%T Study on Techniques of Earthquake Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 29
%N 4
%P 55-58
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An event called prediction in a time series is more important for geophysics and economy problems. The time series data mining is a combination field of time series and data mining techniques. The historical data are collected which has follow the time series methodology, combine the data mining for preprocessing and finally apply the fuzzy logic rules to predict the impact of earthquake. Earthquake prediction has done by historical earthquake time series to investigating the method at first step ago. Huge data sets are preprocessed using data mining techniques. Based on this process data prediction is possible. This paper is focused on statistics and soft computing techniques to analyze the earthquake data.

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Index Terms

Computer Science
Information Sciences

Keywords

Event time series analysis data mining time series data mining soft computing