Traffic Flow Forecast Based on Ga-Gm Model
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Xiaohua Xu, Xiaofei Hu
In recent years, with the increasing number of motor vehicles, traffic jams on urban roads have become more and more serious. Therefore, it is necessary to study road jams to accurately predict traffic flow, which is an important part of intelligent transportation. A ga-gm prediction model is proposed to predict and analyze traffic flow. Through collecting traffic flow data of a city intersection, simulation and prediction are carried out in matlab environment. The results show that the model has good prediction accuracy and certain practical value.
Traffic Flow; Forecast; Neural Network; Ga-Gm Model