Short-term traffic flow prediction based on grid computing pool model

Traffic flow prediction is one of the important research areas in intelligent transportation system. The key point of dynamic route guidance system is the accurate and prompt information about transportation prediction. The article analyses the characteristics of short-term traffic flow prediction, proposes an optimal resource service method that based on grid computing pool model, builds a traffic flow prediction model based on this method, and predicts the traffic by using genetic algorithm based on higher-order generalized neural networks. In the traffic flow prediction process, the optimal resource service method on the basis of grid computing pool model is utilized to automatically request the best CPU under the current status in traffic information platform to perform the prediction, in order to enhance the service quality and efficiency.