动态随机扰动事件下交通网络连边重要度评估
Importance evaluation of edges in transportation network under dynamic and randomly disruptive event
杜永军 1王宁 2张攀 3蔡志强 3乔雄4
作者信息
- 1. 兰州理工大学经济管理学院,甘肃兰州 730050;新加坡国立大学设计与工程学院,新加坡 117576
- 2. 长安大学运输工程学院,陕西西安 710064
- 3. 西北工业大学机电学院,陕西西安 710072
- 4. 兰州理工大学土木工程学院,甘肃兰州 730050
- 折叠
摘要
采用动态贝叶斯重要度的新方法评估了交通网络连边的重要性;应用随机过程理论刻画外部扰动事件的发生过程,并构建了交通网络可靠性模型;利用概率技术,导出了每条连边的动态贝叶斯重要度的计算公式,并确定了其最大值和取得最大值的相应连边;基于该计算公式,设计了数值算法以评估每条连边在不同时刻的动态贝叶斯重要度的值;引进了一个交通网络的实际案例,其连边受到的动态随机扰动冲击过程是一个给定尺度参数和形状参数的饱和非时齐泊松计数过程,演示了动态贝叶斯重要度的计算方法,并对连边的重要性排序关于尺度参数和形状参数的变化进行了敏感性分析.研究结果表明:无论外部随机扰动事件如何变化,网络的单边割是最重要的连边,进一步证实了理论分析的正确性;本文提出的动态贝叶斯重要度能及时精确地识别所有连边的重要性程度,其同时考虑外部随机扰动事件的扰动和网络结构,弥补了传统静态连边重要度仅考虑连边"位置"的缺陷;尺度参数或者形状参数越大,则2条连边的重要性排序的变化越快.
Abstract
A dynamic Bayesian importance measure method was proposed for edge importance evaluation of transpartation network.The random process theory was applied to characterize the generation process of external disruptive events,and a transportation network reliability model was established.Probabilistic techniques were utilized to obtain a formula of dynamic Bayesian importance measure of each network edge,and a maximum value for the importance measure and corresponding maximum edges were determined.Based on the formula,an numerical algorithm was developed to evaluate the Bayesian importance measure of each edge at different times.An actual case of a transportation network was introduced,and the dynamic random disruptive shock process incurred by the edges was a saturated non-time homogeneous Poisson counting process with given scale parameters and shape parameters.The calculation method of dynamic Bayesian importance measure was demonstrated,and the sensitivity analysis of the scale parameter and shape parameter of the importance ranking of the connected edges was made.Research results show that,regardless of the changes in random disruptive events from the external environment,the one-edge cut in the network remains the most important edge,which verifies the correctness of the theoretical analysis.Considering external random disruptive events and the network structure,the Bayesian importance measure can timely and accurately identify the importance of all edges,which fills the gap left by the traditional static measure for edge importance that only considers the position of an edge.As the values of the scale parameters and shape parameters become larger,the importance ranking of the two edges changes faster.1 tab,4 figs,31 refs.
关键词
交通工程/冲击过程/连边故障/扰动事件/动态贝叶斯重要度Key words
traffic engineering/shock process/edge failure/disruptive event/dynamic Bayesian importance measure引用本文复制引用
基金项目
国家自然科学基金项目(72161025)
国家自然科学基金项目(72371035)
陕西省重点研发计划(2023-YBGY-143)
国家留学基金管理委员会项目(202308620190)
出版年
2024
NETL
NSTL
万方数据