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基于接近关联度的城市轨道交通网络动态瓶颈排序方法
引用本文:王智鹏,罗霞.基于接近关联度的城市轨道交通网络动态瓶颈排序方法[J].科技管理研究,2016(17):209-215.
作者姓名:王智鹏  罗霞
作者单位:西南交通大学交通运输与物流学院,四川成都,610031
基金项目:高等学校博士学科点专项科研基金项目“融合多源信息智能感知技术的交通行为事件提取方法”(201301841120),中国铁路总公司科技研究开发计划课题“新一代客票系统技术深化研究——面向新一代客票系统的客运收益管理体系及关键技术研究”(2014X006-A),交通运输部项目“北京综合交通一体化出行服务关键技术研究与应用示范”(2014364x14040)
摘    要:以复杂网络统计特性为基础,构造城市轨道交通网络动态瓶颈排序属性集,建立动态不确定重要型多属性消错排序方法对其排序:引用消错理论,构造各时段错误损失矩阵;分别采用时间度方差法及改进的纵横向拉开档次法,确定时序权重及各时段属性权重;基于灰色综合关联度,以各阶段之间关联度偏差最小为原则,建立时序权重修正模型;通过计算与目标策略及完全错误策略点的改进接近关联度,构造目标函数,确定优属度进行动态瓶颈排序。最后,通过算例验证方法的操作流程和有效性。

关 键 词:复杂网络  动态瓶颈  消错理论  灰色关联度  时序权重  优属度
收稿时间:2015/12/21 0:00:00
修稿时间:2016/8/29 0:00:00

Dynamic Bottleneck Sorting Method of Urban Rail Transit NetworkBased on the Grey Nearness Incidence Degree
Abstract:Based on the statistical feature of complex network, the dynamic bottleneck sort attribute sets of urban rail transit network was constructed. The dynamic uncertain important multiple attribute error-eliminating sorting methods was established, specific operation as follows: the error-loss matrix during various time parts was constructed via citing the error-elimination theory; the weight of stages and attributes was respectively confirmed by using the time degree variability weighting vector method and the improved vertical and horizontal scatter degree method; the minimum correlation deviation between stages as a principle, the weight correction model of time was set up based on the grey correlation degree; dynamic bottleneck was sorted via using the optimal membership degree acquired the established objective function which applied the improved grey nearness incidence degree between with the target strategy and completely wrong strategy. Finally, the operation process and effectiveness of sorting method was validated by an example analysis.
Keywords:complex network  dynamic bottleneck  error-elimination theory  grey correlation degree  time weight  optimal membership degree
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