›› 2009, Vol. 30 ›› Issue (12): 3876-3880.

• Numerical Analysis • Previous Articles     Next Articles

Genetic-least square support vector machine estimation of slope stability

MA Wen-tao1, KONG Liang2   

  1. 1. School of Maths & Computer Engineering, Ningxia University, Yinchuan 750021, China; 2. School of science,Qingdao Technological University, 266033 China
  • Received:2008-01-28 Online:2009-12-10 Published:2010-01-18

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Abstract:

The genetic algorithm is used to search the parameters of least square support vector machine in order to avoid the blindness of manual searching and improve the generalization of the model. Based on the large amount of measured data of practical slope engineering, a genetic-least square support vector machine estimation model of slope stability is set up; and then it is applied to predict the stability factor of natural slope in Dingjiahe phosphorus mine. The agreement of the theoretical results with the actual situation of natural slope shows that the proposed model is effective and reliable.

Key words: slope stability, least square support vector machine, genetic algorithm, parameter selecting

CLC Number: 

  • TU 457
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