Short-Term Traffic Flow Grey Forecasting Model GM(1,1|tan(k-τ)p, sin(k -τ)p) of Single-Cross-Section and Its Particle Swarm Optimization

摘要

This paper is concerned with the question of short-term traffic flow forecasting of single cross-section. The forecasting method is based on GM(1,1 | tan(k - τ)p, sin(k - τ)p)the main reason is taking into account that this model and the traffic flow have two same features: delaying and undulating. This paper analyses the effect of the arameter p in the model, proposes particle swarm optimization algorithm to search the parameter p while the prediction accuracy is the highest. At last, an example shows the method is effective in short-term traffic flow forecasting.