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The application of particle swarm optimization on intelligent transport system

机译:粒子群优化在智能传输系统上的应用

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With analyzing current traffic problems, the passage pointed out that it can effectively avoid traffic jam by adjusting the time of traffic lights. It adapted optimization algorithm to prove the result by building up a model to analysis. The algorithm that we chose was particle swarm optimization, for this algorithm can build up a signal manage system model easily with considering less complicated factors, and it led to the result that we can get the data more accurate. We established a model that simulated crossing conditions. In the processing of algorithm, we altered the traffic problem into a mathematics question. The traffic intersection model that we built was mainly based on intelligent transport system, as intelligent signal manage system was the core of intelligent transport system. The result of the algorithm proved that traffic will be smoother if we can adjust the time of traffic light from red to light reasonably and effectively.
机译:通过分析当前的交通问题,该段落指出,它可以通过调整红绿灯时间来有效避免交通堵塞。它适应了通过构建模型来分析来证明结果的优化算法。我们选择的算法是粒子群优化,对于这种算法可以轻松地建立信号管理系统模型,考虑到较少的复杂因素,它导致了我们可以更准确地获得数据的结果。我们建立了模拟过境条件的模型。在处理算法中,我们将交通问题更改为数学问题。我们构建的流量交叉路口主要是基于智能传输系统,因为智能信号管理系统是智能运输系统的核心。算法的结果证明,如果我们可以合理且有效地调整红绿灯的交通灯时间,交通将更加光滑。

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