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基于混合Copula函数的风雨联合概率分布模型
引用本文:勾红叶,冷丹,王涵玉,蒲黔辉.基于混合Copula函数的风雨联合概率分布模型[J].中国公路学报,2021,34(2):309-316.
作者姓名:勾红叶  冷丹  王涵玉  蒲黔辉
作者单位:1. 西南交通大学土木工程学院, 四川成都 610031;2. 四川建筑职业技术学院交通与市政工程系, 四川成都 610399
基金项目:四川省应用基础研究重点项目(2018JY0549)。
摘    要:特殊地区风雨联合作用下高速铁路桥梁和车辆的气动特性会发生改变,进而影响列车安全舒适运行.为了全面描述风雨联合分布规律和时空关联特征,基于兰新高铁自然灾害监测系统的长时气象监测数据,提出基于混合Copula函数的风雨联合概率分布模型.首先选取Gumbel、Clay-ton和Frank Copula函数建立混合Copula...

关 键 词:桥梁工程  风雨联合概率分布模型  混合Copula函数  参数估计  拟合优度检验
收稿时间:2019-12-06

Joint Probability Distribution Model of Wind Velocity and Rainfall with Mixed Copula Function
GOU Hong-ye,LENG Dan,WANG Han-yu,PU Qian-hui.Joint Probability Distribution Model of Wind Velocity and Rainfall with Mixed Copula Function[J].China Journal of Highway and Transport,2021,34(2):309-316.
Authors:GOU Hong-ye  LENG Dan  WANG Han-yu  PU Qian-hui
Institution:1. School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, Sichuan, China;2. Department of Transport and Municipal Engineering, Sichuan College of Architectural Technology, Chengdu 610399, Sichuan, China
Abstract:The aerodynamic characteristics of high-speed railway bridges and vehicles vary under wind and rain in special areas,then affecting the operation safety and comfort of trains.To comprehensively describe the joint distribution law and spatiotemporal correlation features of wind velocity and rainfall,this paper presents a joint probability distribution model of wind velocity and rainfall with mixed Copula function based on monitoring data from the natural disaster monitoring system of the Lanzhou-Xinjiang high-speed railway.The mixed Copula function was constructed using the Gumbel,Clayton,and Frank Copula functions.The marginal distribution functions of extreme wind velocity and rainfall were then estimated using the nonparametric kernel density estimation method.The weight and dependence parameters of mixed Copula function were estimated according to the Bayesian weighted average method and minimum of sum square variation.The goodness of fit of mixed Copula function was tested using the K-S and minimum distance methods.Finally,taking the monitoring data of the extreme wind velocity and rainfall along the Lanzhou-Xinjiang high-speed railway as an example,the joint probability distribution models of wind velocity and rainfall with different copula functions were established and compared.The results show that the joint probability distribution models of wind velocity and rainfall with mixed Copula function can more accurately describe the various correlations between the extreme wind velocity and rainfall.The joint probability distribution model of wind velocity and rainfall with three mixed Copula functions is the best model to describe the joint distribution law of the extreme wind velocity and rainfall.The correlations between the extreme wind velocity and rainfall monitored by the base station along the Lanzhou-Xinjiang high-speed railway are main left tail,secondary right tail,and secondary symmetry.
Keywords:bridge engineering  joint probability distribution model of wind velocity and rainfall  mixed Copula function  parameter  goodness of fit test
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