应用支持向量机预测公交车运行时间

采用一种新颖的神经网络-支持向量机(SVM),来预测公交车的到站时间,其目的是要验证SVM在运行时间预测领域的可行性.该模型采用了时间段、天气、路段以及当前路段的运行时间和下一路段的最新运行时间5个输入变量.最后,应用大连市开发区4路公交线对该模型进行了校验,并得到若干结论.

Bus Arrival Time Prediction Using Support Vector Machines

Effective prediction of bus arrival time is central to many advanced traveler information system.This paper 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.Time-of-day,weather,segment,the travel time of current segment and the latest travel time of next segment are taken as five 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 some conclusions are drawn.