Evaluation of Liquefaction Potential of Soil Based on Shear Wave Velocity Using Multi-Gene Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InCollection{Muduli:2015:hbgpa,

• author = "Pradyut Kumar Muduli and Sarat Kumar Das",
• title = "Evaluation of Liquefaction Potential of Soil Based on Shear Wave Velocity Using Multi-Gene Genetic Programming",
• booktitle = "Handbook of Genetic Programming Applications",
• publisher = "Springer",
• year = "2015",
• editor = "Amir H. Gandomi and Amir H. Alavi and Conor Ryan",
• chapter = "12",
• pages = "309--343",
• keywords = "genetic algorithms, genetic programming, Multi-gene genetic programming, Shear wave velocity, Liquefaction index, Probability of liquefaction, Bayesian mapping function",
• isbn13 = "978-3-319-20882-4",
• DOI = "doi:10.1007/978-3-319-20883-1_12",
• 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 (V_s) 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 (P_L) with factor of safety (F_s) 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.",

}

Genetic Programming entries for Pradyut Kumar Muduli Sarat Kumar Das

Citations