Site Characterization Model Using Support Vector Machine and Ordinary Kriging

Autor:	Samui Pijush, Das Sarat
Jazyk:	angličtina
Rok vydání:	2011
Předmět:	ordinary kriging semivariogram support vector machine standard penetration test site characterization Science Electronic computers. Computer science QA75.5-76.95
Zdroj:	Journal of Intelligent Systems, Vol 20, Iss 3, Pp 261-278 (2011)
Druh dokumentu:	article
ISSN:	0334-1860 2191-026X
DOI:	10.1515/jisys.2011.014
Popis:	In the present study, ordinary kriging and support vector machine (SVM) have been used to develop three dimensional site characterization model of an alluvial site based on standard penetration test (SPT) results. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing ε-insensitive loss function has been adopted. The knowledge of the semivariogram of the SPT values (N) is used in the ordinary kriging method to predict the N values at any point in the subsurface of the site where field measurements are not available. The comparison between the SVM and ordinary kriging model demonstrates that the SVM model is superior to ordinary kriging model in predicting N values in the site.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/090769f1fa2c4dfda6cca3c78aff5ae6 Zobrazit plný text záznamu View record in DOAJ