基于灰色关联与区间贝叶斯模型的铁路隧道建设质量风险研究
发布时间：2018-08-19 09:56
【摘要】：随着我国社会经济的发展,投资规模巨大、影响范围宽广、涉及技术复杂的大型建设工程项目层出不穷。越来越复杂的工程建设,意味着工程质量的影响因素也会越来越多,对施工的质量管理工作的要求也变得越来越来高。如何应对诸如铁路隧道项目等建设项目施工过程中可能遇到的风险问题,已经成为工程项目质量风险管理工作的重要挑战。 本文以项目风险管理理论框架为依据,采用灰色理论与区间贝叶斯模型相结合的方式,通过风险研究两步走的研究思路,结合某铁路建设中的隧道项目实例,对大型建设项目的质量风险管理进行研究。 针对目前我国建设项目数据缺乏,质量风险管理工作复杂的特点,论文通过将灰色理论以及区间贝叶斯模型应用到工程的质量风险识别以及评价决策工作中,运用组合赋权的灰色关联法从具有贫信息的特征工程项目质量问题中挖掘工程项目的风险因素并加以排序；将风险识别中得到的权重指标与区间贝叶斯模型相结合,运用区间值对风险的描述能力以及贝叶斯概率的修正能力,完成对施工方案的质量风险评价工作,为项目施工方案决策提供参考意见。本文采用了某铁路隧道工程项目的质量风险管理实例,证明了该方法模型的有效性,并依此为大型建设项目的风险管理工作提出建议和指导。 本文旨在引入从整体风险识别到实际风险评价的质量风险管理思路,通过使用灰色理论与区间贝叶斯模型,组成一套可以应用于诸如铁路隧道等大型建设工程质量风险管理的方法。通过合理的风险指标识别帮助项目管理工作者有针对性地对可能造成质量问题的因素采取合理的防范和管控措施,利用风险指标的评价提高施工方案的质量控制,从而进一步提升质量风险管理工作的有效性和可操作性。期待本文使用的理论方法模型能够在我国的建设工程质量风险管理工作中发挥其指导效用。
[Abstract]:With the development of our country's social economy, the investment scale is huge and the scope of influence is wide. The more and more complex project construction, means the engineering quality influence factor also will be more and more, to the construction quality management work request also becomes more and more high. How to deal with the possible risks in construction such as railway tunnel projects has become an important challenge in the quality risk management of engineering projects. Based on the theoretical framework of project risk management and the combination of grey theory and interval Bayesian model, this paper combines a tunnel project in a railway construction with a two-step approach to risk research. Research on quality risk management of large construction projects. In view of the lack of construction project data and the complexity of quality risk management in our country, this paper applies grey theory and interval Bayesian model to project quality risk identification and evaluation decision. The grey relation method of combinatorial weight is used to excavate the risk factors of engineering projects from the quality problems of characteristic engineering projects with poor information, and to combine the weights obtained in risk identification with the interval Bayes model. Using the ability of interval value to describe the risk and the ability of Bayesian probability to modify the risk, the quality risk evaluation of the construction scheme is completed, and the reference for the project construction scheme decision is provided. In this paper, an example of quality risk management in a railway tunnel project is used to prove the validity of the model and to provide advice and guidance for the risk management of large construction projects. The purpose of this paper is to introduce the idea of quality risk management from whole risk identification to actual risk evaluation, by using grey theory and interval Bayesian model. A set of methods can be applied to the quality risk management of large construction projects such as railway tunnels. Through the reasonable risk index identification, the project manager can take reasonable prevention and control measures to the factors that may cause the quality problem, and use the evaluation of the risk index to improve the quality control of the construction scheme. In order to further improve the effectiveness and operability of quality risk management. It is expected that the theoretical model used in this paper can play a guiding role in the quality risk management of construction projects in China.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U455.1
本文编号：2191315
[Abstract]:With the development of our country's social economy, the investment scale is huge and the scope of influence is wide. The more and more complex project construction, means the engineering quality influence factor also will be more and more, to the construction quality management work request also becomes more and more high. How to deal with the possible risks in construction such as railway tunnel projects has become an important challenge in the quality risk management of engineering projects. Based on the theoretical framework of project risk management and the combination of grey theory and interval Bayesian model, this paper combines a tunnel project in a railway construction with a two-step approach to risk research. Research on quality risk management of large construction projects. In view of the lack of construction project data and the complexity of quality risk management in our country, this paper applies grey theory and interval Bayesian model to project quality risk identification and evaluation decision. The grey relation method of combinatorial weight is used to excavate the risk factors of engineering projects from the quality problems of characteristic engineering projects with poor information, and to combine the weights obtained in risk identification with the interval Bayes model. Using the ability of interval value to describe the risk and the ability of Bayesian probability to modify the risk, the quality risk evaluation of the construction scheme is completed, and the reference for the project construction scheme decision is provided. In this paper, an example of quality risk management in a railway tunnel project is used to prove the validity of the model and to provide advice and guidance for the risk management of large construction projects. The purpose of this paper is to introduce the idea of quality risk management from whole risk identification to actual risk evaluation, by using grey theory and interval Bayesian model. A set of methods can be applied to the quality risk management of large construction projects such as railway tunnels. Through the reasonable risk index identification, the project manager can take reasonable prevention and control measures to the factors that may cause the quality problem, and use the evaluation of the risk index to improve the quality control of the construction scheme. In order to further improve the effectiveness and operability of quality risk management. It is expected that the theoretical model used in this paper can play a guiding role in the quality risk management of construction projects in China.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U455.1
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