广义神经网络的研究及其在交通流预测中的应用

Research of generalized neural network and it′s application to traffic flow prediction

提出一种基于线性独立函数的智能神经元模型 ,理论分析表明这种智能神经元比普通神经元具有更高的知识存储能力 ,可使整个神经网络的信息处理能力得到大大增强。将这种智能神经元组成的广义神经网络应用于交通流预测 ,对大连市实测交通流数据进行了预测分析。实验结果表明 ,该广义神经网络的预测效果远远优于常规 BP网络 ,具有较高的实用价值。

Intelligent neuron model based on linear independent function is presented. It is proved that this intelligent neuron has greater knowledge storing capacity than normal neuron and can strengthen the information processing capability of neural network. Traffic flow data of Dalian city is predicted by meansofsuchneuralnetwork. Experiment results show that generalized neural network gains the advantage over BP network.