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

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

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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.

中文概要

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。

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Authors and Affiliations

  1. State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean, and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Ze-xiang Wu & Hui Ji

  2. Department of Civil Engineering, Wenzhou University, Wenzhou, 325035, China

    Chuang Yu

  3. State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower Engineering, Sichuan University, Chengdu, 610065, China

    Cheng Zhou

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  1. Ze-xiang Wu
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  2. Hui Ji
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  4. Cheng Zhou
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Correspondence to Hui Ji.

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Project supported by the National Natural Science Foundation of China (No. 41002091)

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Wu, Zx., Ji, H., Yu, C. et al. EPR-RCGA-based modelling of compression index and RMSE-AIC-BIC-based model selection for Chinese marine clays and their engineering application. J. Zhejiang Univ. Sci. A 19, 211–224 (2018). https://doi.org/10.1631/jzus.A1700089

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