神经网络流量预测模型 multifractal FIR network ; MF-FIR
本文将BP网络模型与灰色系统预测方法相结合，建立了公交客流量预测模型。
This article establish a forecast model of passenger volume in the public transportation by combine with gray system estimate and the BP networks model.
与传统的公交客流量预测方法相比，本模型预测结果具有更高的精度。
With traditional forecast method compare, the accuracy of this model forecast result is higher.
实际的城市交通流量预测研究表明，该模型具有较高的预测精度，可以为城市交通规划和控制提供准确的参考。
Practical prediction research of urban traffic flow shows that this model has famous predicted precision, and it can provide exact reference for urban traffic programming and control.
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