中国海相黏土的压缩指数的EPR-RCGA回归模型和RMSE-AIC-BIC模型选择及其工程应用（英文）

EPR-RCGA-based modelling of compression index and RMSE-AIC-BIC-based model selection for Chinese marine clays and their engineering application

目的:压缩指数是软土工程领域的关键参数。本文旨在提出一个基于进化多项式回归和实编码遗传算法(EPR-RCGA)的回归分析方法,将压缩指数与物理特性建立相关关系并应用于工程实践。创新点:结合EPR和RCGA方法,将中国沿海21个不同区域的黏土的压缩性指数与天然含水率和液塑限之间建立相关关系,并采用均方根误差(RMSE)、赤池信息量准则(AIC)和贝叶斯信息准则(BIC)对所建立的不同回归模型进行优选。方法:1.从文献中收集中国沿海21个地区的黏土的压缩指数和常见的基本物理性质,并对数据进行整理和分类。2.进行压缩指数和天然含水量及液塑限之间的EPR回归关系分析,并采用新近提出的RCGA优化方法来提高回归关系的精度。3.采用RMSE、AIC和BIC对不同组合下的回归关系进行优选,并确定最佳回归关系。4.将得到的关系式应用到有限元路堤计算来验证所得关系式的实用性和准确性。结论:1.本文提出的压缩指数关系式比现有的经验公式更好,预测得到的压缩指数更为精确。2.采用所提出的压缩指数回归模型预测了东南沿海一路堤下不同土层的压缩指数,并应用所得数据和有限元方法对路堤的沉降进行了模拟分析,验证了所提方法的可靠性。3.所有结果表明,结合基于EPR和RCGA的回归分析方法以及基于RMSE、AIC和BIC的模型选择方法对分析压缩指数与黏土的物理性质的相关关系是切实可行的,可以更好地服务于中国沿海地区的工程设计。

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.