Chapter
Jul 11, 2012
Method to Predict Slope Safety Factor Using SVM
Publication: Earth and Space 2012: Engineering, Science, Construction, and Operations in Challenging Environments
Abstract
Support vector machine (SVM) is an identification method using the largest classification margin between classes of the training samples as its classification criteria. The final value of decision function of general classified SVM only depends on the inner product in Hibert space after transformation of input parameters into higher dimensional space. In this paper, the decision function of SVM is used as the synthetic affect factor on slope stability, and the regression equation of the decision function and safety factor of the training samples is proposed to be utilized to predict the slope safety factor.
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Published In
Earth and Space 2012: Engineering, Science, Construction, and Operations in Challenging Environments
Pages: 888 - 899
Copyright
© 2012 American Society of Civil Engineers.
History
Published online: Jul 11, 2012
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State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering of Hohai University, P.O. Box 210098, Nanjing, PR China. E-mail: [email protected]
College of Water Conservancy and Hydropower Engineering, Hohai University, P.O. Box 210098, Nanjing, PR China. E-mail: [email protected]
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.