News
Received the Student Paper Award at IPSJ-SIGUBI 62th workshop
July 05, 2019
The following paper won the Student Paper Award at IPSJ-SIGUBI 62th workshop （http://sigubi.ipsj.or.jp/excellent/：external link).
Predicting Urban Dynamics with GPS data by Multi-Order Poisson Regression Model Chen Yanru*, Yuta Hayakawa*, Kota Tsubouchi, Masamichi Shimosaka* *Tokyo Institute of Technology
We propose a Multi-Order Poisson Regression Model for urban dynamics prediction based on an enriched and generalized feature representation. In the proposed method, new features are produced by employing a variety of polynomial combinations of multiple factors which greatly affect people flow (e.g., time-of-the-day, day-of-the-week, weather situation, holiday information). The results obtained from an experiment with a massive GPS dataset show that the proposed method is capable of producing models which have higher prediction accuracy compared to the state-of-the-art method.