Online Predictive Model for Taxi Services

Author:

Moreira-Matias Luís,Gama João,Ferreira Michel,Mendes-Moreira João,Damas Luís

Publisher

Springer Berlin Heidelberg

Reference17 articles.

1. Glashenko, A., Ivaschenko, A., Rzevski, G., Skobelev, P.: Multiagent real time scheduling system for taxi companies. In: Proceedings of 8th Int. Conf. on Autonomous Agents and Multi-Agent Systems, Budapest, Hungary (2009)

2. Lecture Notes in Computer Science;J. Lee,2007

3. Junghoon, L., Inhye, S., Park, G.: Analysis of the Passenger Pick-Up Pattern for Taxi Location Recommendation. In: Conference on Networked Computing and Advanced Information Management, vol. 1, pp. 199–204 (2008)

4. Bin, L., Daqing, Z., Lin, S., Chao, C., Shijian, L., Guande, Q., Qiang, Y.: Hunting or waiting? Discovering passenger-finding strategies from a large-scale real-world taxi dataset. In: 2011 IEEE International Conference on Pervasive Computing and Communications Workshops, pp. 63–68 (2011)

5. Ihler, A., Hutchins, J., Smyth, P.: Adaptive Event Detection with Time-Varying Poisson Processes. In: 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, pp. 207-216 (2006)

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1. A novel dynamically adjusted regressor chain for taxi demand prediction;2020 International Joint Conference on Neural Networks (IJCNN);2020-07

2. Phase Transition in Taxi Dynamics and Impact of Ridesharing;Transportation Science;2020-01-01

3. A Unified Framework with Multi-source Data for Predicting Passenger Demands of Ride Services;ACM Transactions on Knowledge Discovery from Data;2019-12-31

4. On Predicting the Taxi-Passenger Demand: A Real-Time Approach;Progress in Artificial Intelligence;2013

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