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Bus Arrival Time Prediction Using Support Vector Machines

机译:支持向量机的公交车到站时间预测

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Effective prediction of bus arrival time is central to many advanced traveler information systems. This article presents support vector machines (SVM), a new neural network algorithm, to predict bus arrival time. The objective of this paper is to examine the feasibility and applicability of SVM in vehicle travel time forecasting area. Segment, the travel time of current segment, and the latest travel time of next segment are taken as three input features. Bus arrival time predicted by the SVM is assessed with the data of transit route number 4 in Dalian economic and technological development zone in China and conclusions are drawn.
机译:有效预测公交车的到站时间对于许多高级旅行者信息系统而言至关重要。本文介绍了支持向量机(SVM),这是一种新的神经网络算法,可以预测公交车的到站时间。本文的目的是检验支持向量机在车辆行驶时间预测领域的可行性和适用性。段,当前段的行进时间和下一段的最新行进时间被视为三个输入要素。利用中国大连经济技术开发区的4号公交线路数据,对SVM预测的公交车到达时间进行了估算。

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