Efficiency of pile groups installed in cohesionless soil using artificial neural networks

Adel M. Hanna, George Morcous, Mary Helmy

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


This paper presents an artificial neural network (ANN) model that predicts the efficiency of pile groups installed in cohesionless soil and subjected to axial loading. The model accounts for the planar geometry of the group (pile diameter, pile spacing, and pile arrangement) and incorporates the effect of pile installation, pile length, cap condition, soil condition, and type of loading on the group efficiency. The results produced by the proposed ANN model compared well with the available results of laboratory and field tests. The ANN model is a viable design tool that assists foundation engineers in predicting the pile group efficiency in an accurate and realistic manner. In addition, this model can be easily updated to incorporate new data and accommodate new design parameters.

Original languageEnglish (US)
Pages (from-to)1241-1249
Number of pages9
JournalCanadian Geotechnical Journal
Issue number6
StatePublished - Dec 2004
Externally publishedYes


  • Artificial neural networks
  • Axial load
  • Cohesionless soil
  • Group efficiency
  • Pile foundation

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Geotechnical Engineering and Engineering Geology


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