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Directional Signage Location Optimization of Subway Station Based on Big Data

机译:基于大数据的地铁站定向标牌位置优化

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摘要

The imperfection of the guide signs in the subway will lead to many difficulties for passengers, which directly affects the operation efficiency of subway stations. In this paper, we use big data to analyze the problem of signages in Beijing subway, and propose the optimization model of signages in subway stations based on particle swarm optimization algorithm. The experimental results of Dongzhimen subway station in Beijing show that the model has strong robustness in optimization, and the global best position can be found 100 & x0025;.
机译:地铁中指南标志的不完美会导致乘客的困难,这直接影响地铁站的运营效率。在本文中,我们使用大数据来分析北京地铁的标牌问题,并提出了基于粒子群优化算法的地铁站标牌的优化模型。北京东正地铁站的实验结果表明,该模型在优化方面具有强大的稳健性,全球最佳地位100&X0025;

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