›› 2005, Vol. 26 ›› Issue (3): 404-408.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Application of neural network based on simulated annealing Gauss-Newton algorithm to seepage back analysis

LIU Xian-shan1, ZHOU Chuang-bin1, ZHANG Li-jun2   

  1. 1.State Key Laboratory of Water Resurces and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; 2.Zhanghe Hydranlic Project Administration Bureau, Jingmen 448156, China
  • Received:2003-10-10 Online:2005-03-10 Published:2013-11-21

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Abstract: Simulated Annealing Gauss-Newton algorithm applied to neural network is put forward. It overcomes some limitation of the traditional BP neural network. Taking iterative convergence of sine function for example, the correction, efficiency and superiority of the algorithm are proved. At the same time, this algorithm is applied to seepage back analysis of Tongleping dam, using seepage coefficient to calculate seepage flow field. And forecasted water heads approach to the observed values, which illuminates the back analysis result is correct and the algorithm is feasible in the practical seepage parameters identification.

Key words: simulated annealing Gauss-Newton algorithm, back analysis, seepage coefficient

CLC Number: 

  • TV 223.6
  • 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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