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基于数字孪生与多目标粒子群的轨道交通网拓扑结构模型

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针对当前轨道交通网拓扑结构模型动态调度能力较差,导致轨道交通线路拥堵的问题,构建基于数字孪生与多目标粒子群的轨道交通网拓扑结构模型.将目标区域基础信息整合为样本网格线统计量,选择城市轨道交通样本网格线.应用数字孪生技术分析轨道交通线路运行状态,实现轨道交通动态调节.使用多目标粒子群算法根据目标函数对模型进行优化,得到最终交通网拓扑结构模型.至此,基于数字孪生与多目标粒子群的轨道交通网拓扑结构模型设计完成.构建实验环节,验证此模型应用效果.实验结果表明,此模型形态特征优于当前模型,在一定程度上降低了线路的拥堵程度,提升了交通运输水平.
Topology Model of Rail Transit Network Based on Digital Twins and Multi-objective Particle Swarm Optimization
The current rail transit network topology model has poor dynamic scheduling ability,which leads to rail transit line congestion,a rail transit network topology model based on digital twins and multi-objective particle swarm optimization is con-structed.It integrates the basic information of the target area into the sample grid line statistics,and selects the sample grid line of urban rail transit.Digital twin technology is applied to analyze the running state of rail transit lines to realize the dynamic adjustment of rail transit.The multi-objective particle swarm optimization algorithm is used to optimize the model according to the objective function,and the final traffic network topology model is obtained.So far,the design of the topology model of rail transit network based on digital twins and multi-objective particle swarm optimization is completed.We build an experimental link to verify the application effect of this model.The experimental results show that the morphological characteristics of this model are better than the current model,and can reduce the congestion of the line to a certain extent and improve the level of transportation.

digital twinmulti-objective particle swarmrail transit networktopologytraffic volume predictiontraffic delay analysis

杨迎卯

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温州市铁路与轨道交通投资集团有限公司,浙江,温州 325000

数字孪生 多目标粒子群 轨道交通网 拓扑结构 交通量预测 交通延误分析

2024

微型电脑应用
上海市微型电脑应用学会

微型电脑应用

CSTPCD
影响因子:0.359
ISSN:1007-757X
年,卷(期):2024.40(7)