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Topics:Traffic Big Data Analytics and Mining: Preliminary Practices in Xiamen
Abstract: Various traffic big data has been emerging in big cities, such as road networks, GPS trajectories of buses and taxicabs, traffic flows, accidents, road maintenances, etc. Thus, how to fuse the massive traffic big data combining with rich context-aware information (time, location, and spatio-temporal correlations) becomes both a big engineering and research challenge. In this presentation, I will introduce the “Traffic Big Data Analytics and Mining in Xiamen” project, including preliminary results such as traffic congestion index, accident data analytics and visualization, short-time traffic flow prediction based on deep learning algorithm, and OD analytics. The result of traffic big data analytics and mining will benefit both the government and police officers in facilitating the traffic management, traffic congestion identification and traffic flow prediction, as well as minimizing accident severity as well.
CV:
Dr. Xiaoliang Fan received his Ph. D. degree in computing science from University Pierre and Marie CURIE (University Paris 6), France in 2012. Currently, he works at School of Information Science & Engineering in Lanzhou University in China as an Assistant Professor. He also works as a Post-doc fellow at Fujian Key Laboratory of Sensing and Computing for Smart Cities, Xiamen University. His research interests include traffic big data analytics, context-aware recommender system, etc. He has published 30+ international journal and conference papers. He is member of ACM, IEEE, IEEE CS, CCF, and vice chairman of China-France Software Association.
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