Title: A kind of slope stability evaluation model based on SVM-DS method

Authors: Feng Tian; Hengmao Pang; Xiaoping Sun; Chuanyun Wang

Addresses: School of Control Science and Engineering, Shenyang Aerospace University, Shenyang 024-89723975, China ' School of Control Science and Engineering, Shenyang Aerospace University, Shenyang 024-89723975, China ' School of Computer Science, Liaoning Shihua University, Fushun, 024-56865005, China ' School of Control Science and Engineering, Shenyang Aerospace University, Shenyang 024-89723975, China

Abstract: This paper provides a recognition method based on support vector machine and D-S evidence theory to get the state of the slope stability timely and accurately. Firstly, the classification of effective recognition model is established by limited empirical data using support vector machine approach. And then the sigmoid function is used to achieve the posterior probability output, which serves as the basic probability assignment in the D-S evidence theory of the model. Therefore, the categorised results are outputted when all the information of evidence is fused according to D-S theory. So the predicted slope stability model of SVM-DS is achieved. The proposed method is tested on a dataset of known slope. The experiment results confirm that this method can greatly enhance the classification accuracy of slope stability.

Keywords: slope stability; support vector machines; SVM; D-S theory of evidence; DST; Dempster–Shafer theory; posterior probability; classification accuracy.

DOI: 10.1504/IJAACS.2015.069573

International Journal of Autonomous and Adaptive Communications Systems, 2015 Vol.8 No.2/3, pp.141 - 149

Received: 31 Jan 2013
Accepted: 29 Jul 2013
Published online: 27 May 2015 *

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