基于模糊粗糙神经网络的交通流研究

交通流预测是实现道路交通科学管理的重要内容,文章概述了模糊粗糙神经网络的基本原理,通过模糊粗糙隶属函数建立了基于模糊粗糙神经网络的交通流控制模型,设计了两级协调模糊控制器,结合模糊控制理论和神经网络各自的优点,构造了模糊粗糙神经网络.通过实践结果证明,该算法精度高,学习速度快,适应能力强,对实时交通流预测有一定的指导意义.

Study of Traffic Flow Prediction Based on Fuzzy Rough Neural Network

Traffic flow forecasting is the important content of scientific management of road traffic, in this paper, the basic principle of fuzzy rough neural network was summarized, the traffic flow control model was established based on the fuzzy rough neural network, two level coordination fuzzy controller was designed, and the fuzzy rough neural network was constructed by combination of the advantage of fuzzy control theory and neural network. Through the practice, the results show that, the algorithm has high precision, fast speed, strong adaptable ability and is of certain guiding significance for the real time traffic flow prediction.