POI-LSTM
Taxi Demand Prediction using an LSTM-based Deep Sequence Model and Points of Interest
In this paper, an LSTM-based deep sequence learning model is applied to forecast taxi-demand in a particular urban area in a smart city.
For this purpose, points of interest (POIs) in the city are extracted from Google Maps and integrated with the mobility data sources
Bahman Askari, Tai Le Quy, Eirini Ntoutsi. Taxi Demand Prediction using an LSTM-based Deep Sequence Model and Points of Interest. In 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)..