Application of Quantitative Analysis Method in Traffic Volume Prediction

Predictive analysis about China railway parcel is an urgent task for railway intelligent transportation system (RITS). This paper proposes a novel parcel traffic volume predictive method named FCP (fuzzy cell prediction), which provides an effective means to build strategic models and enhances the predictive ability of interactive and hierarchical analysis. The key components of FCP are traffic data process mode which map variable to infinite spaces. The variable multiple correlation problem are solved. Applications to maximize transport capacity suggest that FCP is a contributive and powerful tool for the RITS.