[期刊论文]


Evaluation of liquefaction potential of soil based on standard penetration test using multi-gene genetic programming model

作   者:
Pradyut K. Muduli;Sarat K. Das;

出版年:2014

页     码:529 - 543
出版社:Springer Nature


摘   要:

This paper discusses the evaluation of liquefaction potential of soil based on standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). The liquefaction classification accuracy (94.19%) of the developed liquefaction index (LI) model is found to be better than that of available artificial neural network (ANN) model (88.37%) and at par with the available support vector machine (SVM) model (94.19%) on the basis of the testing data. Further, an empirical equation is presented using MGGP to approximate the unknown limit state function representing the cyclic resistance ratio (CRR) of soil based on developed LI model. Using an independent database of 227 cases, the overall rates of successful prediction of occurrence of liquefaction and non-liquefaction are found to be 87, 86, and 84% by the developed MGGP based model, available ANN and the statistical models, respectively, on the basis of calculated factor of safety (F s) against the liquefaction occurrence.



关键字:

liquefaction index ;standard penetration test ;limits state function ;artificial intelligence ;multi-gene genetic programming ;factor of safety


所属期刊
Acta Geophysica
ISSN: 1895-6572
来自:Springer Nature