Techno Press
Techno Press

Geomechanics and Engineering
  Volume 1, Number 3, September 2009 , pages 259-262
DOI: https://doi.org/10.12989/gae.2009.1.3.259
 

Pullout capacity of small ground anchors: a relevance vector machine approach
Pijush Samui and T.G. Sitharam

 
Abstract
    This paper examines the potential of relevance vector machine (RVM) in prediction of pullout capacity of small ground anchors. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The results are compared with a widely used artificial neural network (ANN) model. Overall, the RVM showed good performance and is proven to be better than ANN model. It also estimates the prediction variance. The plausibility of RVM technique is shown by its superior performance in forecasting pullout capacity of small ground anchors providing exogenous knowledge.
 
Key Words
    relevance vector machine; small ground anchor; pullout capacity; artificial neural network.
 
Address
Pijush Samui: Department of Civil Engineering, Tampere University of Technology, Tampere, Finland
T.G. Sitharam: Department of Civil Engineering, Indian Institute of Science, Bangalore-560012, India
 
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