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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.

References
  1. United States of Geological Survey http://earthquake.usgs.gov
  2. A. Morales-Esteban, F. Martinez- Alvarez, A. Troncoso, J.L. Justo, C. Rubio-Escudero, Pattern recognition to forecast seismic time series, Elsevier (2010).
  3. Feature extraction, ArcView GIS Version 3.1.
  4. J. S. R. Jang, C. T. Sun and E. Mizutani. Neuro-Fuzzy and Soft Computing. Prentice Hall, 1997. ,
  5. I.Aydin, M. Karakose and E.Akin, The Prediction Algorithm Based on Fuzzy Logic Using Time Series Data Mining Method.
  6. H. Kantz and T. Schreiber, Nonlinear Time Series Analysis, Cambridge: Cambridge University Press, 388 p., 1997.
  7. J. Han and M. Kamber, Data Mining: Concepts and Techniques, San Francisco: Academic Press, 800 p., 2005
  8. R. J. Povinelli, “Time Series Data Mining: Identifying Temporal Patterns for Characterization and Prediction of Time Series Events”, Ph.D. Dissertation, Marquette University, 180 p., 1999.
  9. Chris gray, A Review of Two Methods of Predicting Earthquakes.
  10. A. Morales- Esteban, F. Martinez-Alvarez, A. Troncoso, J.L.Justo, C. Rubio-Escudero, Pattern recognition to forecast seismic time series, Elsevier, Experts System with Application 37(2010) 8333 – 8342
  11. Muhammad Ardalani-Farsa, Saeed Zolfaghari, Chaotic time series prediction with residual analysis method using hybrid Elman–NARX neural networks, Elsevier, Neuro computing 73 (2010) 2540-2553.
  12. Scott J. Goetz, Gregory J. Fiske, Andrew G. Bunn, Using satellite time-series data sets to analyze fire disturbance and forest recovery across Canada, Remote Sensing of Environment 101 (2006) 352–365.
  13. Hao-Tien Liu, Mao-Len Wei, An improved fuzzy forecasting method for seasonal time series, Expert Systems with Applications 37 (2010) 6310–6318.
  14. G. Peter Zhang, Time series forecasting using a hybrid ARIMA and neural network model, Neuro computing 50 (2003) 159 – 175.
  15. T. Takagi, M. Sugeno, "Fuzzy identification of systems and its applications to modeling and control," IEEE Trans. Syst., Man Cyber, vol. 15, pp 116-132, 1985
  16. Arash Andalib, Mehdi Zare, Farid Atry, a fuzzy expert system for earthquake prediction, case study: the zagros range, ICMSAO 2009
  17. Neeti Bhargava, V. K. Katiyar, M. L. Sharma and P. Pradhan, Earthquake Prediction through Animal Behavior: A Review, Indian Journal of Biomechanics: Special Issue (NCBM 7-8 March 2009).
  18. J Sajjad Mohsin, Faisal Azam, Computational seismic algorithm comparison for earthquake prediction. International Journal of Geology, Issue 3, Volume 5, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

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