Abstract
In this chapter, liquefaction potential of soil is evaluated within deterministic as well as probabilistic framework based on the post-liquefaction shear wave velocity (Vs) measurement data using a soft computing technique, multi-gene genetic programming (MGGP), which is a variant genetic programming (GP). On the basis of the developed limit state function by the MGGP, a mapping function is presented to correlate probability of liquefaction (PL) with factor of safety (Fs) against liquefaction using Bayesian theory of conditional probability. Two examples are presented to compare the developed MGGP-based deterministic as well as probabilistic methods with those of available artificial neural network (ANN)-based methods. The findings from the above two examples confirm that MGGP-based methods are more accurate than the ANN-based methods in predicting the liquefied as well as non-liquefied cases.
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