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首页> 外文期刊>Neural computing & applications >Comparison of artificial bee colony and flower pollination algorithms in vehicle delay models at signalized intersections
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Comparison of artificial bee colony and flower pollination algorithms in vehicle delay models at signalized intersections

机译:信号交叉口在车辆延迟模型中的人工蜂菌落和花粉算法的比较

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摘要

Delay is a significant research topic since it includes indicators such as travel quality, lost time and fuel consumption. Furthermore, the delay is used for optimization of traffic control systems and determination of the level of service at signalized intersections. Therefore, researchers have focused on accurate estimation of delay. The objective of this study is to simply and accurately estimate the delay and evaluate the performance of the proposed approaches which are artificial bee colony (ABC) and flower pollination algorithms (FPA). In this study, ABC and FPA have been used to develop different delay models which are linear, semi-quadratic, quadratic and power forms. Analysis period (T), the green ratio (g/C; effective green to cycle length) and the degree of saturation (x = v/c; volume to capacity) are used as input parameters while developing the models. The results of present models are compared to estimations obtained from analytical models which are Highway Capacity Manual and Australian (Akcelik) delay models. Semi-quadratic form yielded to best results in terms of coefficient of determination (R-2), mean square error and mean absolute error. Additionally, FPA approach showed better performance than ABC approach finding the optimal solution in the lower number of iterations.
机译:延迟是一个重要的研究主题,因为它包括旅行质量,损失时间和燃料消耗等指标。此外,延迟用于优化交通控制系统和确定信号交叉点的服务水平。因此,研究人员专注于准确估计延迟。本研究的目的是简单准确地估计延迟并评估所提出的方法是人造群菌落(ABC)和花授粉算法(FPA)的性能。在本研究中,ABC和FPA已被用于开发不同的延迟模型,该模型是线性,半二次,二次和动力形式。分析周期(t),绿色比率(g / c;有效绿色到循环长度)和饱和度(x = v / c;容量)在开发模型时用作输入参数。将现有模型的结果与来自分析模型获得的估计进行比较,这是高速公路容量手册和澳大利亚(Akcelik)延迟模型。半二次形式在确定系数(R-2),均方误差和平均绝对误差方面得到最佳结果。此外,FPA方法显示出比ABC方法更好的性能,在较低的迭代中找到最佳解决方案。

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