Short-Term Traffic Volume Prediction Based on Gray Wolf Optimization Algorithm

This paper takes the data of the intersection of Jianghai Avenue and North Street as an example and proposes a short-term traffic flow prediction model (DGWO-GRU) based on the hyperbolic tangent-improved gray wolf algorithm (DGWO) to optimize the GRU neural network. Through historical speed and flow data, weather data and working day dataset, predict the future traffic volume, so as to provide an important decision basis for the traffic guidance system.