神经网络在智能公交实时调度中的设计与实现

Design and Implementation of Neural Network in the Real-time Scheduling of Intelligent Transportation

神经网络是一种新兴的数学建模方法,它具有识别复杂非线性系统的特性,比较适合实时调度。在智能公交实时调度中加入误差反向传播算法,利用误差反向传播算法超强的学习能力和泛化能力,通过对海量公交历史调度数据的学习,可以建立公交车到达目的站点的预测模型;通过实时GPS数据,就可以预测车辆到达目的地的大概时间,为建立智能公交调度提供极大方便。

Neural network is a new new kind of mathematical modeling method, it has characteristic of identifying complex non-linear system, and is suitable for real-time scheduling. Join error back propagation algorithm into intelligent transportation real-time scheduling, using its superior learning ability and generalization ability, through learning the history of mass transit scheduling data, can establish the forecast model of bus arrival at the site. Through real-time GPS data, can predict the approximate time the vehicle reaches the destination, providing great convenience for the establishment of in- telligent transportation scheduling.