CLC number: TU433
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2018-01-31
Cited: 0
Clicked: 5624
Ze-xiang Wu, Hui Ji, Chuang Yu, Cheng Zhou. EPR-RCGA-based modelling of compression index and RMSE-AIC-BIC-based model selection for Chinese marine clays and their engineering application[J]. Journal of Zhejiang University Science A, 2018, 19(3): 211-224.
@article{title="EPR-RCGA-based modelling of compression index and RMSE-AIC-BIC-based model selection for Chinese marine clays and their engineering application",
author="Ze-xiang Wu, Hui Ji, Chuang Yu, Cheng Zhou",
journal="Journal of Zhejiang University Science A",
volume="19",
number="3",
pages="211-224",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1700089"
}
%0 Journal Article
%T EPR-RCGA-based modelling of compression index and RMSE-AIC-BIC-based model selection for Chinese marine clays and their engineering application
%A Ze-xiang Wu
%A Hui Ji
%A Chuang Yu
%A Cheng Zhou
%J Journal of Zhejiang University SCIENCE A
%V 19
%N 3
%P 211-224
%@ 1673-565X
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1700089
TY - JOUR
T1 - EPR-RCGA-based modelling of compression index and RMSE-AIC-BIC-based model selection for Chinese marine clays and their engineering application
A1 - Ze-xiang Wu
A1 - Hui Ji
A1 - Chuang Yu
A1 - Cheng Zhou
J0 - Journal of Zhejiang University Science A
VL - 19
IS - 3
SP - 211
EP - 224
%@ 1673-565X
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1700089
Abstract: The compression index is a key parameter in the field of soft clay engineering. In this paper, we propose an improved method for correlating the compression index with the physical properties of intact Chinese marine clays that are involved in many construction projects in coastal regions in China. First, the compression index and some common physical properties of clays from 21 regions along the Chinese coast are extracted from the literature. Then, a basic regression analysis for the compression index using the natural water content and atterberg limits is conducted. To improve the correlation performance, an evolutionary polynomial regression (EPR) and real coded genetic algorithm (RCGA) combined technique is adopted to formulate different equations involving different numbers of variables. An optimal correlation using only natural water content and liquid limit as input parameters is finally selected according to the root mean square error (RMSE), Akaike’s information criterion (AIC), and Bayesian information criterion (BIC). The proposed correlation is evaluated and shown to perform better than existing empirical correlations in predicting the compression index for all selected Chinese marine clays. This correlation is validated to be reliable and applicable to engineering applications through the prediction of the properties of an embankment on the southeast coast of China using finite element method. All comparisons show that the EPR and RCGA combined technique is powerful for correlating the compression index with the physical properties of the clay, and that model selection by RMSE, AIC, and BIC is effective. The proposed correlation could be used to update current formulations, and is applicable to engineering design in coastal regions of China.
It is an interesting work of application of an optimisation method to determine compressibility parameter of Chinese marine clay. The optimal correlation using only natural water content and liquid limit is selected according to the RMSE, AIC and BIC . The proposed correlation is evaluated in better performance than existing empirical correlations on predicting the compression index for all selected Chinese marine clays. This correlation is validated using finite element method. The EPR and RCGA combined technique is powerful for the correlation of compression index by physical properties of clay.
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