摘要
为了建立完善的公交系统,提出了基于GA-Elman的公交到站时间预测模型,进行公交到站时间预测.模型中以时间段、天气、路段和当前路段运行时间为输入量,以福州市第20路公交车为例进行验证.验证结果表明,该模型比单纯用Elman神经网络的预测模型计算量小,能够较准确地进行公交到站时间预测.
To improve public traffic system, a model of arrival time forecasting for public transport vehicles based on GA-Elman is proposed in this paper. The result of using this model to predict the arrival time in the future based on No. 20 Bus Route in Fuzhou shows that the GA-Elman neural network is more precise and effective in making short-term prediction than Elman neural network.
出处
《厦门理工学院学报》
2012年第1期71-74,共4页
Journal of Xiamen University of Technology
基金
福建省教育厅B类项目(JB09245)
福建交通职业技术学院科教研发基金(09KY16)