城市轨道交通正线信号灯显示的优化模型分析  

Optimization Model Analysis of Signal Light Display in Main Line of Urban Rail Transit

作　　者：李雪 LI Xue(School of Rail Transportation,Shandong Jiaotong University,Jinan 250000,China)

机构地区：[1]山东交通学院,轨道交通学院,山东济南250000

出　　处：《微型电脑应用》2025年第2期219-221,共3页Microcomputer Applications

摘　　要：为了提升城市轨道交通正线运输能力,在瞬时大旅客吞吐量情况下提升城市轨道交通运行稳定性,提出一种优化模型。在加大信号灯密度的前提下,引入多列模糊对抗神经网络,包括模糊神经网络模块、对数神经网络模块、超限学习机神经网络模块等子模块,优化城市轨道交通正线信号灯显示控制算法,并对信号灯控制策略算法进行仿真分析。仿真实验结果表明,该算法可以有效提升城市轨道交通的旅客吞吐能力,且在大旅客吞吐量需求和高密度发车需求下,系统脆弱度评价结果得到有效优化。In order to improve the transportation capacity of urban rail transit on the main line,improve the operation stability of urban rail transit under the condition of instantaneous large passenger throughput,this paper presents an optimization model.Under the premise of increasing the density of signal lights,this paper introduces multi-column fuzzy adversarial neural network,including sub-modules such as fuzzy neural network module,logarithmic neural network module,and limit learning machine neural network module,to optimize the urban rail transit main line signal light display control algorithm,and simulates and analyzes the signal light control strategy algorithm.Simulation experimental results show that the algorithm can effectively improve the passenger throughput capacity of urban rail transit,and the system vulnerability evaluation results are effectively optimized under the demand of large passenger throughput and high-density departure.

关 键 词：城市轨道交通 正线信号灯 显示控制算法 仿真分析 神经网络 人工智能 

分 类 号：TM425[电气工程—电器]