On the basis of macroscopic dynamic traffic flow model which is frequently used in traffic control, Radial basis Function (RBF) neural network is designed.

根据常用的高速公路交通流宏观动态模型，建立了高速公路交通流的RBF神经网络模型。

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Then, aiming at the existing problem, the algorithm of dynamic recurrent neural network, RBF neural network and adaptive inverse control is studied in the paper.

接着，结合其存在的问题，对动态递归神经网络、R BF神经网络和自适应逆控制进行了算法研究。

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A new method was represented to model dynamic linear regression system driven by data, in which a bayesian network was combined with the RBF neural network.

结合贝叶斯网络和神经网络，提出了一种建立数据驱动型的动态线性回归系统模型的方法。

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