| 突发事件下高速铁路区间通过能力计算 |
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| 引用本文： | 王莉,秦勇,徐杰,贾利民.突发事件下高速铁路区间通过能力计算[J].北京理工大学学报,2013,33(S1):18-21. |
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| 作者姓名： | 王莉 秦勇 徐杰 贾利民 |
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| 作者单位： | 北京交通大学 轨道交通控制与安全国家重点实验室, 北京 100044;北京交通大学 交通运输学院, 北京 100044;北京交通大学 轨道交通控制与安全国家重点实验室, 北京 100044;北京交通大学 轨道交通控制与安全国家重点实验室, 北京 100044;北京交通大学 轨道交通控制与安全国家重点实验室, 北京 100044 |
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| 基金项目： | 国家自然科学基金资助项目(61074151);国家科技支撑计划项目(2009BAG12A10) |
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| 摘 要： | 分析突发事件条件下区间通过能力计算涉及的不确定因素. 针对其动态性、模糊性、随机性及无后效性等特点,建立了基于马尔可夫链的区间通过能力计算方法. 当特殊运营条件发生或列车运行受到随机干扰时,利用模糊评判法建立状态转移矩阵,而后根据列车速度对路网能力进行快速折算. 实验证明,基于马尔科夫链的能力计算方法更能容错各类不确定性因素,可预测未来某时段的路网通过能力.
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| 关 键 词： | 突发事件 区间通过能力 模糊随机过程 马尔科夫链 |
| 收稿时间： | 7/8/2013 12:00:00 AM |
Section Carrying Capacity Calculation in Emergency for High-Speed Railway |
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| WANG Li,QIN Yong,XU Jie and JIA Li-min.Section Carrying Capacity Calculation in Emergency for High-Speed Railway[J].Journal of Beijing Institute of Technology(Natural Science Edition),2013,33(S1):18-21. |
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| Authors: | WANG Li QIN Yong XU Jie and JIA Li-min |
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| Institution: | Rail Traffic Control and Safety State Key Laboratory, Beijing Jiaotong University, Beijing 100044, China;School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China;Rail Traffic Control and Safety State Key Laboratory, Beijing Jiaotong University, Beijing 100044, China;Rail Traffic Control and Safety State Key Laboratory, Beijing Jiaotong University, Beijing 100044, China;Rail Traffic Control and Safety State Key Laboratory, Beijing Jiaotong University, Beijing 100044, China |
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| Abstract: | Uncertainties parameters of section carrying capacity calculation in emergency were analyzed. The capacity calculation method is established according to characteristics of dynamic, fuzziness, randomness and non-aftereffect property based on fuzzy Markov chain. When encountering with the special operating conditions or random interference, the state transition matrix is established by fuzzy evaluation method, and then railway network capacity is calculated in good time based on the train speed. The case study shows that the capacity calculation method based on fuzzy Markov chain was more tolerant types of uncertainties, which are fit for predicting the railway network through capacity in future period. |
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| Keywords: | emergency section carrying capacity fuzzy random process Markov chain |
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