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ISRN Soil Science
Volume 2012 (2012), Article ID 346439, 10 pages
http://dx.doi.org/10.5402/2012/346439
Research Article

Three-Dimensional Site Characterization Model of Bangalore Using Support Vector Machine

Centre for Disaster Mitigation and Management, VIT University, Vellore 632014, India

Received 9 December 2011; Accepted 17 January 2012

Academic Editors: W. Ding and Z. He

Copyright © 2012 Pijush Samui. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The main objective of site characterization is the prediction of in situ soil properties at any half-space point at a site based on limited tests. In this study, the Support Vector Machine (SVM) has been used to develop a three dimensional site characterization model for Bangalore, India based on large amount of Standard Penetration Test. SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing ε-insensitive loss function. The database consists of 766 boreholes, with more than 2700 field SPT values ( 𝑁 ) spread over 220 sq km area of Bangalore. The model is applied for corrected 𝑁 ( 𝑁 𝑐 ) values. The three input variables ( π‘₯ , 𝑦 , and 𝑧 , where π‘₯ , 𝑦 , and 𝑧 are the coordinates of the Bangalore) were used for the SVM model. The output of SVM was the 𝑁 𝑐 data. The results presented in this paper clearly highlight that the SVM is a robust tool for site characterization. In this study, a sensitivity analysis of SVM parameters (σ, 𝐢 , and ε) has been also presented.