Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
CPT-based probabilistic evaluation of seismic soil liquefaction potential using multi-gene genetic programming
In this paper, liquefaction potential of soil is evaluated within a probabilistic framework based on the post-liquefaction cone penetration test (CPT) data using an evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). Based on the developed limit state function using MGGP, a relationship is given between probability of liquefaction (PL) and factor of safety against liquefaction using Bayesian theory. This Bayesian mapping function is further used to develop a PL-based design chart for evaluation of liquefaction potential of soil. Using an independent database of 200 cases, the efficacy of the present MGGP-based probabilistic method is compared with that of the available probabilistic methods based on artificial neural network (ANN) and statistical methods. The proposed method is found to be more efficient in terms of rate of successful prediction of liquefaction and non-liquefaction cases, in three different ranges of PL values compared to ANN and statistical methods.
CPT-based probabilistic evaluation of seismic soil liquefaction potential using multi-gene genetic programming
In this paper, liquefaction potential of soil is evaluated within a probabilistic framework based on the post-liquefaction cone penetration test (CPT) data using an evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). Based on the developed limit state function using MGGP, a relationship is given between probability of liquefaction (PL) and factor of safety against liquefaction using Bayesian theory. This Bayesian mapping function is further used to develop a PL-based design chart for evaluation of liquefaction potential of soil. Using an independent database of 200 cases, the efficacy of the present MGGP-based probabilistic method is compared with that of the available probabilistic methods based on artificial neural network (ANN) and statistical methods. The proposed method is found to be more efficient in terms of rate of successful prediction of liquefaction and non-liquefaction cases, in three different ranges of PL values compared to ANN and statistical methods.
CPT-based probabilistic evaluation of seismic soil liquefaction potential using multi-gene genetic programming
Muduli, Pradyut Kumar (Autor:in) / Das, Sarat Kumar (Autor:in) / Bhattacharya, Subhamoy (Autor:in)
02.01.2014
15 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
CPT-based Seismic Liquefaction Potential Evaluation Using Multi-gene Genetic Programming Approach
| Springer Verlag | 2013
CPT-based Seismic Liquefaction Potential Evaluation Using Multi-gene Genetic Programming Approach
| Online Contents | 2014
| British Library Online Contents | 2015