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Feasibility improvement of transportation for light rail train system

机译:轻轨列车系统运输可行性的改进

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A single track train system generally follows a queuing model from end to end as trains generally falls in line from one station to the other then back. The effect of this model, as experienced in the Light Rail Transit (LRT) Train system, is waiting time to board train coaches take longer for passenger in the middle stations of the track since the first trains were already optimized during the first two to three stations. With the advent of researches in swarm intelligence applied to optimization problems. This research looks into a swarm of trains with a single objective instead of trains queuing on the tracks to load and unload based on range of frequencies. The research investigated using Poisson simulation an alternative Ant algorithm model applied to autonomous trains in the system as such improve the public service of transporting passengers. The research used the simulation data based from actual volume of use from the LRT line 1 system and will only focus on peak-hours experienced in the system.
机译:单轨列车系统通常从一端到另一端遵循排队模型,因为列车通常从一个站到另一站,然后又在后面成一直线。正如在轻轨运输(LRT)火车系统中所经历的那样,此模型的效果是等待登车的火车教练要花更长的时间在轨道的中间车站,因为第一批火车已经在前两到三趟中进行了优化站。随着研究群体智能应用于优化问题。这项研究着眼于一群具有单一目标的火车,而不是根据频率范围在轨道上排队进行装卸的火车。该研究使用Poisson仿真方法研究了一种可替代的Ant算法模型,该模型应用于系统中的自动列车,从而改善了运送乘客的公共服务。该研究使用了基于LRT 1号线系统实际使用量的模拟数据,并且仅关注系统中的高峰时间。

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