abstract = "Liquefaction of soil is one of the major causes for
the significant damages to the buildings, lifeline
systems and harbor facilities caused by the
earthquakes. At present artificial intelligence
techniques such as artificial neural network (ANN) and
support vector machine (SVM) based models are found to
be more efficient compared to statistical methods. The
present study discusses about the evaluation of
liquefaction potential of soil based on cone
penetration test (CPT) data obtained after 1999
Chi-Chi, Taiwan, earthquake using evolutionary
artificial intelligence technique known as genetic
programming (GP). A comparative study is made among the
existing three CPT based statistical methods and the
developed GP model for prediction of liquefied and
non-liquefied cases in terms of percentage success rate
with respect to the field observations.",
notes = "Civil Engineering Department, NIT, Rourkela,
India.
https://gndec.ac.in/~igs/ldh/conf/2011/prelims.pdf
Theme-N: Numerical and Physical Modelling Paper No.
N-082",