摘要
介绍了出租车保有量神经网络预测模型的建立.以南京市的实际数据为检测依据,论证了该模型应用于城市出租汽车保有量预测的可行性,并对该市2005～2008年的出租汽车保有量进行了预测;该预测模型与传统模型进行预测对比的结果表明,由于神经网络在处理非线性系统方面的优越性,该预测模型在交通预测方面具有较高的计算精度.
In this paper a new solution algorithm based on BP neural network is developed for the urban taxi services forecast, whose feasibility is testified by real time data collected in Nanjing. The city＇s taxi services through years 2005 to 2008 are forecast. Compared with conventional models, this new one has more advantages in nonlinear modeling and a better future in transportation prediction.
出处
《交通与计算机》
2005年第5期35-37,共3页
Computer and Communications
