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Nash Model Parameter Uncertainty Analysis by AM-MCMC Based on BFS and Probabilistic Flood Forecasting

Chinese Geographical Science 2011年第1期21卷 74-83页

作者： XING Zhenxiang RUI Xiaofang FU Qiang JIYi ZHU Shijiang Department of Water Conservancy & Civil Engineering Northeast Agriculture University Harbin 150030 China Key Laboratory for Water-saving Agriculture of Universities in Heilongjiang Province Harbin 150030 China Department of Hydrology Hohai University Nanjing 210098 China

A hydrologic model consists of several parameters which are usually calibrated based on observed hy-drologic processes. Due to the uncertainty of the hydrologic processes, model parameters are also uncertain, which further leads to the uncertainty of forecast results of a hydrologic model. Working with the Bayesian Forecasting System (BFS), markov chain monte carlo simulation based Adaptive Metropolis method (AM-MCMC) was used to study parameter uncertainty of Nash model, while the probabilistic flood forecasting was made with the simu-lated samples of parameters of Nash model. The results of a case study shows that the AM-MCMC based on BFS proposed in this paper is suitable to obtain the posterior distribution of the parameters of Nash model according to the known information of the parameters. The use of Nash model and AM-MCMC based on BFS was able to make the probabilistic flood forecast as well as to find the mean and variance of flood discharge, which may be useful to estimate the risk of flood control decision.

关键词： Bayesian Forecasting System parameter uncertainty markov chain monte carlo simulation Adaptive Metropolis method probabilistic flood forecasting

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Updating the models and uncertainty of mechanical parameters for rock tunnels using Bayesian inference

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Geoscience Frontiers 2021年第5期12卷 224-236页

作者： Hongbo Zhao Bingrui Chen Shaojun Li Zhen Li Changxing Zhu School of Civil and Architectural Engineering Shandong University of TechnologyZibo 255000ShandongChina State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan 430071HubeiChina School of Civil Engineering Henan Polytechnic UniversityJiaozuo 454003China

Rock mechanical parameters and their uncertainties are critical to rock stability analysis,engineering design,and safe construction in rock mechanics and *** back analysis is widely adopted in rock engineering to determine the mechanical parameters of the surrounding rock mass,but this does not consider the *** problem is addressed here by the proposed approach by developing a system of Bayesian inferences for updating mechanical parameters and their statistical properties using monitored field data,then integrating the monitored data,prior knowledge of geotechnical parameters,and a mechanical model of a rock tunnel using markov chain monte carlo(MCMC)*** proposed approach is illustrated by a circular tunnel with an analytical solution,which was then applied to an experimental tunnel in Goupitan Hydropower Station,*** mechanical properties and strength parameters of the surrounding rock mass were modeled as random *** displacement was predicted with the aid of the parameters updated by Bayesian inferences and agreed closely with monitored *** indicates that Bayesian inferences combined the monitored data into the tunnel model to update its parameters *** study indicated that the performance of Bayesian inferences is improved greatly by regularly supplementing field monitoring *** inference is a significant and new approach for determining the mechanical parameters of the surrounding rock mass in a tunnel model and contributes to safe construction in rock engineering.

关键词： Rock tunnel engineering Back analysis Bayesian inference Uncertainty analysis markov chain monte carlo simulation

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基于动态Copula的企业集团信用风险传染效应研究

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管理科学 2019年第6期

作者：周利国何卓静蒙天成

企业集团成员企业间基于业务关联、技术关联和财务关联的相互联系，构成了企业信用风险传染的重要渠道。金融机构如果缺乏对企业集团成员企业间信用风险传染的管理和防控意识，其后果可能是金融机构信贷资产遭受巨大经济损失。本文基于... 详细信息

企业集团成员企业间基于业务关联、技术关联和财务关联的相互联系，构成了企业信用风险传染的重要渠道。金融机构如果缺乏对企业集团成员企业间信用风险传染的管理和防控意识，其后果可能是金融机构信贷资产遭受巨大经济损失。本文基于尾部相依性的视角构建动态协变量Joe-Clayton copula模型，实证分析企业集团成员企业信用风险传染问题。研究发现，信用风险在企业集团成员企业间存在传染效应，且这种信用风险传染效应呈现一定的动态特征；宏观经济因素和微观公司经营能力、财务状况对企业集团内部不同组别子企业间信用风险传染效应的影响从重要性程度和作用方向两个维度上存在差异。

关键词：信用风险传染尾部相依性 Joe-Clayton copula markov chain monte carlo模拟企业集团 credit risk contagion tail-dependence Joe-Clayton copula markov chain monte carlo simulation enterprise group

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