• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 17 Issue 2
Apr.  2009
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Article Contents
GUANQin-chuan, ZHANG Zhi-yong, FENGHao. Artificial Neural Network Forecast Model for SlopeDeformation of Large-Scale Dry-Doc[J]. Journal of Southwest Jiaotong University, 2004, 17(2): 157-161.
Citation: GUANQin-chuan, ZHANG Zhi-yong, FENGHao. Artificial Neural Network Forecast Model for Slope Deformation of Large-Scale Dry-Doc[J]. Journal of Southwest Jiaotong University, 2004, 17(2): 157-161.

Artificial Neural Network Forecast Model for Slope Deformation of Large-Scale Dry-Doc

  • Publish Date: 25 Apr 2004
  • Factors influencing the deformation of a dry-dock slope were analyzed. They are soil mass strength, time of non-protection slope, gradient of slope, number of layout excavation, depth of layout excavation, excavation step, rainfall depth and load on slope top. Based on the above and the typical deformation data measured in-situ, an artificial neural network model of predicting the deformation of a dry- dock slope was proposed, and the prediction result is consistent with the measured in-situ result. In addition, the vigilance values for slope deformation for the expanding slope technology, the four judgement modes for slope deformation and their corresponding control measures were put forward.

     

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      沈阳化工大学材料科学与工程学院 沈阳 110142

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