The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges.Therefore,determining the optimal stre...The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges.Therefore,determining the optimal stress spectrum model is crucial for further fatigue reliability analysis.This study investigates the performance of the REBMIX algorithm in modeling both univariate(stress range)and multivariate(stress range and mean stress)distributions of the rain-flowmatrix for a steel arch bridge,usingAkaike’s Information Criterion(AIC)as a performance metric.Four types of finitemixture distributions—Normal,Lognormal,Weibull,and Gamma—are employed tomodel the stress range.Additionally,mixed distributions,including Normal-Normal,Lognormal-Normal,Weibull-Normal,and Gamma-Normal,are utilized to model the joint distribution of stress range and mean stress.The REBMIX algorithm estimates the number of components,component weights,and component parameters for each candidate finite mixture distribution.The results demonstrate that the REBMIX algorithm-based mixture parameter estimation approach effectively identifies the optimal distribution based on AIC values.Furthermore,the algorithm exhibits superior computational efficiency compared to traditional methods,making it highly suitable for practical applications.展开更多
The classical risk process that is perturbed by diffusion is studied. The explicit expressions for the ruin probability and the surplus distribution of the risk process at the time of ruin are obtained when the claim ...The classical risk process that is perturbed by diffusion is studied. The explicit expressions for the ruin probability and the surplus distribution of the risk process at the time of ruin are obtained when the claim amount distribution is a finite mixture of exponential distributions or a Gamma (2, α) distribution.展开更多
The broadleaved-Korean pine mixed forest is a native vegetation in the Changbai Mountains,northeast China.The probability density functions including the normal,negative exponential,Weibull and finite mixture distribu...The broadleaved-Korean pine mixed forest is a native vegetation in the Changbai Mountains,northeast China.The probability density functions including the normal,negative exponential,Weibull and finite mixture distribution,were used to describe the diameter distributions of the species groups and entire forest stand.There is a strong correlation between parameters and mean DBH except the shape parameters in the mixture distribution.The diameter classes of species and entire forest stand showed not negative exponential but normal and"S"distribution.The mixture function was better than normal and Weibull to describe the model distribution.The location parameter had an effect on the estimated frequency in the first diameter class,when the estimated location parameter was bigger than the lower limit of the first diameter class.展开更多
基金jointly supported by the Fundamental Research Funds for the Central Universities(Grant No.xzy012023075)the Zhejiang Engineering Research Center of Intelligent Urban Infrastructure(Grant No.IUI2023-YB-12).
文摘The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges.Therefore,determining the optimal stress spectrum model is crucial for further fatigue reliability analysis.This study investigates the performance of the REBMIX algorithm in modeling both univariate(stress range)and multivariate(stress range and mean stress)distributions of the rain-flowmatrix for a steel arch bridge,usingAkaike’s Information Criterion(AIC)as a performance metric.Four types of finitemixture distributions—Normal,Lognormal,Weibull,and Gamma—are employed tomodel the stress range.Additionally,mixed distributions,including Normal-Normal,Lognormal-Normal,Weibull-Normal,and Gamma-Normal,are utilized to model the joint distribution of stress range and mean stress.The REBMIX algorithm estimates the number of components,component weights,and component parameters for each candidate finite mixture distribution.The results demonstrate that the REBMIX algorithm-based mixture parameter estimation approach effectively identifies the optimal distribution based on AIC values.Furthermore,the algorithm exhibits superior computational efficiency compared to traditional methods,making it highly suitable for practical applications.
文摘The classical risk process that is perturbed by diffusion is studied. The explicit expressions for the ruin probability and the surplus distribution of the risk process at the time of ruin are obtained when the claim amount distribution is a finite mixture of exponential distributions or a Gamma (2, α) distribution.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.70373044 and 30470302)China's Ministry of Science and Technology(04EFN216600328)the Northeast Rejuvenation Program of the Chinese Academy of Sciences.
文摘The broadleaved-Korean pine mixed forest is a native vegetation in the Changbai Mountains,northeast China.The probability density functions including the normal,negative exponential,Weibull and finite mixture distribution,were used to describe the diameter distributions of the species groups and entire forest stand.There is a strong correlation between parameters and mean DBH except the shape parameters in the mixture distribution.The diameter classes of species and entire forest stand showed not negative exponential but normal and"S"distribution.The mixture function was better than normal and Weibull to describe the model distribution.The location parameter had an effect on the estimated frequency in the first diameter class,when the estimated location parameter was bigger than the lower limit of the first diameter class.
