A Study of Earthquake mining using Support Vector Machine

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-35 Number-1
Year of Publication : 2016
Authors : D.Sakthivel, M.Premkumar
  10.14445/22312803/IJCTT-V35P106

MLA

D.Sakthivel, M.Premkumar "A Study of Earthquake mining using Support Vector Machine". International Journal of Computer Trends and Technology (IJCTT) V35(1):36-37, May 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
An Earthquake is more important for geophysics and economy problems. The Support Vector Machine of data mining techniques with cluster analysis is used to predict impact of earthquake [2]. The historical data are collected which has follow the time series methodology, combine the data mining for pre-processing and finally apply the SVM 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 [1]. This paper is focused on statistics and soft computing techniques to analyze the earthquake data.

References
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Keywords
Earthquake liquefaction; seismic subsidence; building settlements; support vector classification.