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Geomechanics and Engineering
  Volume 3, Number 4, December 2011 , pages 285-290
DOI: https://doi.org/10.12989/gae.2011.3.4.285
 


Multivariate adaptive regression spline applied to friction capacity of driven piles in clay
Pijush Samui

 
Abstract
    This article employs Multivariate Adaptive Regression Spline (MARS) for determination of friction capacity of driven piles in clay. MARS is non-parametric adaptive regression procedure. Pile length, pile diameter, effective vertical stress, and undrained shear strength are considered as input of MARS and the output of MARS is friction capacity. The developed MARS gives an equation for determination of fs of driven piles in clay. The results of the developed MARS have been compared with the Artificial Neural Network. This study shows that the developed MARS is a robust model for prediction of fs of driven piles in clay.
 
Key Words
    multivariate adaptive regression spline; driven pile; clay; friction capacity; artificial neural network.
 
Address
Pijush Samui: Centre for Disaster Mitigation and Management, VIT University, Vellore-632014, India
 

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