摘要
针对二维独立分布不能考虑变量间相关性,导致堤防边坡稳定性的可靠度计算结果不够准确的问题,基于171组长江堤防岸线土体抗剪强度试验数据,采用Copula函数研究长江堤防岸线土体抗剪强度参数间相关性,利用AIC、BIC准则识别最优边缘分布与Copula函数,构建二维联合分布模型,并分析数据量对参数间相关结构识别的影响。结果表明,基于Copula函数的二维联合分布模型能够较准确地表征长江堤防岸线土体参数间的相关性;当数据量大于24组时,AIC、BIC准则可准确识别最优Copula函数,为堤防边坡可靠度计算和Copula函数模型的构建提供参考。
Aiming at the problem that the reliability calculation results of embankment slope stability are not accurate due to the fact that the correlation between variables cannot be considered in two-dimensional independent distribution, based on 171 sets of test data of the shear strength of the Yangtze River embankment shoreline soil, Copula function was used to study the correlation between the shear strength parameters of the Yangtze River embankment shoreline soil. The AIC and BIC criteria were used to identify the optimal edge distribution and Copula function, and a two-dimensional joint distribution model was constructed. The influence of data volume on the identification of correlation structure between parameters was analyzed. The results show that the two-dimensional joint distribution model based on Copula function can accurately characterize the correlation between soil parameters of the Yangtze River embankment shoreline;When the data volume is more than 24 groups, AIC and BIC criteria can accurately identify the optimal Copula function, which provides a reference for the reliability calculation of embankment slope and the construction of Copula function model.
作者
殷永鑫
杨文东
周鑫隆
胡少华
YIN Yong-xin;YANG Wen-dong;ZHOU Xin-long;HU Shao-hua(School of Safety Science and Emergency Management,Wuhan University of Technology,Wuhan 430070,China;School of Resources and Environmental Engineering,Wuhan University of Technology,Wuhan 430070,China;School of Civil Engineering,Architecture and Environment,Hubei University of Technology,Wuhan 430068,China)
出处
《水电能源科学》
北大核心
2023年第2期202-206,共5页
Water Resources and Power
基金
国家自然科学基金项目(52108315)
湖北省教育厅科学技术研究计划青年人才项目(Q20211404)
湖北省自然科学基金项目(2021CFB286)。
关键词
COPULA函数
堤防
抗剪强度参数
边缘分布
联合概率分布模型
Copula function
embankment
shear strength parameters
marginal distribution
joint probability distribution model
