S. Atalla

Data-Driven Multi-Horizon Taxi Demand Forecasting Using Transformer-Based Temporal Modeling

This work studies multi-horizon taxi demand prediction as the task of learning a mapping from past observations to multiple future demand values under temporal dependence and uncertainty, and suggests that successful multi-horizon forecasting requires global temporal interaction and explicit quantification of uncertainty.