›› 2008, Vol. 29 ›› Issue (8): 2236-2240.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Evaluation of slope stability based on SOFM neural network

XUE Xin-hua1, ZHANG Wo-hua1, LIU Hong-jun2   

  1. 1. Key Laboratory of Soft Soils and Geoenvironmental Engineering, Ministry of Education, Zhejiang University, Hangzhou 310027, China; 2. Department of Geoenvironmental Engineering, Ocean University of China, Qingdao 266003, China
  • Received:2006-12-08 Online:2008-08-11 Published:2013-08-02

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Abstract: Considering uncertainty of parameter in slope stability analysis, an improved algorithm for self-organizing feature map(SOFM) neural network is presented to increase the convergence speed and capability, and a SOFM neural network model for evaluating the status of the slope stability is established based on the improved algorithm. Then, the SOFM neural network model is trained and checked with the collected slope analyzing examples, and compared with results obtained by the BP neural network. The results show that the SOFM neural network presents excellent network performance, high prediction accuracy; and it is an effective way to evaluate the stability of slopes.

Key words: self-organization feature map, neural network, slope stability, evaluation

CLC Number: 

  • TU 413.6
  • Please send e-mail to pingzhou3@126.com if you would like to read full paper in English for free. Parts of our published papers have English translations.
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