›› 2004, Vol. 25 ›› Issue (10): 1569-1574.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Neural network approach for prediction of liquefaction potential of two-dimensional site

SHE Yue-xin   

  1. 1.Huaiyin Institute of Technology, Huaian 223001, China; 2. Research Institute of Geotechnical Engineering, Hohai University, Nanjing 210098, China
  • Received:2003-06-25 Online:2004-10-11 Published:2014-07-25

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Abstract: The prediction model for liquefaction potential of site based on artificial neural networks is presented. The spatial data structural characteristics of liquefaction potential of site can be mapped by different spread values. The optimal spread value can be determined by means of cross-validation technique of geostatistics. Study results indicate that the generalized regression neural networks can map the structural characteristics of liquefaction potential under the condition of the optimal spread. The result obtained is consistent with that of Kriging estimator. The model can be applied to the prediction of two-dimensional spatial data and the decision system based on GIS.

Key words: liquefaction potential, neural networks, geostatistics, site, prediction

CLC Number: 

  • TU19.5
  • 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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