Research on Taxi Demand Prediction Based on Deep Learning and Multi-Types of Data

Accurate prediction of taxi demand is crucial for the decision-making process of ride-hailing platforms. Many studies are limited to small-scale analyses and neglect city-wide demand forecasting. This research utilizes deep learning to comprehensively forecast taxi demand in New York City and designs both regional and city-wide modules, overcoming the limitations of focusing on small areas and ignoring the heterogeneity among urban regions. This approach provides a comprehensive and accurate prediction of taxi demand.