Data Mining Techniques for Earthquake Frequency-Magnitude Analysis and Seismic Zone Estimation

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-25 Number-3
Year of Publication : 2015
Authors : Dr.K.Srujan Raju, Kandukuri Rajesh
  10.14445/22312803/IJCTT-V25P122

MLA

Dr.K.Srujan Raju, Kandukuri Rajesh "Data Mining Techniques for Earthquake Frequency-Magnitude Analysis and Seismic Zone Estimation". International Journal of Computer Trends and Technology (IJCTT) V25(3):114-117, July 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
India has had a number of the world's greatest earthquakes in the last century. In fact, more than 50% area in the country is considered prone to damaging earthquakes. The northeastern region of the country as well as the entire Himalayan belt is susceptible to great earthquakes of magnitude more than 8.0. The main cause of earthquakes in these regions is due to the movement of the Indian plate towards the Eurasian plate at the rate of about 50 mm per year. The earthquake zoning map of India divides India into 4 seismic zones (Zone 2, 3, 4 and 5). According to the present zoning map, Zone 5 expects the highest level of seismicity whereas Zone 2 is associated with the lowest level of seismicity. In this Paper, we have derived regression relations on Earthquake Magnitude-frequency Data Set using statistical tools like SAS (Statistical Analysis System) and Weka (Waikato Environment for Knowledge Analysis). The regression relations obtained are the first relations for this region. In Earthquake Disaster Management Data Set, Magnitude is considered as a Dependent variable. It depends on LocationRank, StateRank, Elevation, Population, Year, Month, Day, Hour, Minute, Sec, Latitude, Longitude and Depth which are considered as Independent Variables. Based on Dependent and Independent variables, the new ‘seismic zone’ can be analyzed at different earthquake locations. If magnitude is equal to 7 or more, large areas are damaged depending on their depth. If magnitude is equal to 3 or less, the probability of occurrence of an earthquake is weak.

References
[1] Introduction to Building a Linear Regression Model Leslie A. Christensen the Goodyear Tire & Rubber Company, Akron Ohio.http://www2.sas.com/proceedings/sugi22/STATS/PAPER2 67.PDF
[2] SAS Library, Overview of SAS PROC REG http://www.ats.ucla.edu/stat/sas/library/SASReg_mf.htm [3] SAS Annotated Output, Regression Analysis
http://www.ats.ucla.edu/stat/sas/output/reg.htm [4] SAS Annotated Output, Proccorr http://www.ats.ucla.edu/stat/sas/output/corr.htm
[5] The REG Procedure http://support.sas.com/documentation/cdl/en/statug/63033/HTM L/default/viewer.htm#reg_toc.htm
[6] Earthquake zones of India https://en.wikipedia.org/wiki/Earthquake_zones_of_India
[7] Seven Factors That Contribute to the Destructiveness of an Earthquake http://www.smithsonianmag.com/sciencenature/ seven-factors-that- contribute-to-the-destructiveness-ofan- earthquake-44395116/?no-ist
[8] The Steps to Follow in a Multiple Regression Analysis Theresa Hoang Diem Ngo, La Puente, CA http://support.sas.com/resources/papers/proceedings12/333- 2012.pdf
[9] Earthquake Environment for Physical Design: A Statistical Analysis By S. C. LIU and L. W. FAGEL
[10] Statistics of Indian earthquakes - Frequency energy distribution R . K . S. CIIOUHAN - Y. K . SHRIVASTAVA Received on December 20th, 1973
[11] M.Satish, D.Sridhar, “Prediction of Heart Diseases in Data Mining Techniques” International Journal of Computer Trends and Technology (IJCTT) – volume 24 number 1– June 2015

Keywords
Dependent variable, Independent variable, Seismicity, SAS, Weka.