›› 2004, Vol. 25 ›› Issue (1): 73-76.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

An evolutionary neural network model for suction prediction of unsaturated soils

ZHANG Chuan-qing, YANG Qing, LUAN Mao-tian   

  1. School of Civil and Hydraulic Engineering and State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
  • Received:2002-09-23 Online:2004-01-10 Published:2014-07-15

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Abstract: By combining genetic algorithm and artificial neural network, an evolutionary neural network model is established for the suction prediction of unsaturated soil. In the model, total density, initial water content, pressure preconsolidated and void ratio are considered. The predicted results, which were obtained through the created model, indicate that this model is well in accord with the test data. It provides a new approach for the research of predicting the shear strength of unsaturated soils.

Key words: suction, neural network, genetic algorithm

CLC Number: 

  • TU 4
  • 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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