BRIGHT - Drift-Aware Demand Predictions for Taxi Networks (Extended Abstract)
暂无分享,去创建一个
Erik Jenelius | Amal Saadallah | Jihed Khiari | Joao Gama | Luis Moreira-Matias | Ricardo Sousa | João Gama | E. Jenelius | Jihed Khiari | A. Saadallah | R. Sousa | L. Moreira-Matias
[1] Nicholas Jing Yuan,et al. T-Finder: A Recommender System for Finding Passengers and Vacant Taxis , 2013, IEEE Transactions on Knowledge and Data Engineering.
[2] Hadi Fanaee-T,et al. Event labeling combining ensemble detectors and background knowledge , 2014, Progress in Artificial Intelligence.
[3] W. Hoeffding. Probability Inequalities for sums of Bounded Random Variables , 1963 .
[4] Mohieddine Jelali,et al. Revision of the Tennessee Eastman Process Model , 2015 .
[5] Chang Yang,et al. The Rich and the Poor: A Markov Decision Process Approach to Optimizing Taxi Driver Revenue Efficiency , 2016, CIKM.
[6] João Gama,et al. Hierarchical Clustering of Time-Series Data Streams , 2008, IEEE Transactions on Knowledge and Data Engineering.
[7] João Gama,et al. A system for analysis and prediction of electricity-load streams , 2009, Intell. Data Anal..
[8] Siyuan Liu,et al. HUNTS: A Trajectory Recommendation System for Effective and Efficient Hunting of Taxi Passengers , 2013, 2013 IEEE 14th International Conference on Mobile Data Management.
[9] Hui Xiong,et al. An energy-efficient mobile recommender system , 2010, KDD.
[10] Daqing Zhang,et al. From taxi GPS traces to social and community dynamics , 2013, ACM Comput. Surv..
[11] Erik Jenelius,et al. BRIGHT—Drift-Aware Demand Predictions for Taxi Networks , 2020, IEEE Transactions on Knowledge and Data Engineering.
[12] Daqing Zhang,et al. Urban Traffic Modelling and Prediction Using Large Scale Taxi GPS Traces , 2012, Pervasive.
[13] E. S. Page. CONTINUOUS INSPECTION SCHEMES , 1954 .
[14] Saso Dzeroski,et al. Learning model trees from evolving data streams , 2010, Data Mining and Knowledge Discovery.
[15] João Gama,et al. Ensemble learning for data stream analysis: A survey , 2017, Inf. Fusion.
[16] N. Lawrence Ricker,et al. Decentralized control of the Tennessee Eastman Challenge Process , 1996 .
[17] Jie Xu,et al. ZEST: A Hybrid Model on Predicting Passenger Demand for Chauffeured Car Service , 2016, CIKM.
[18] Emmanouil Chaniotakis,et al. Informed Versus Non-Informed Taxi Drivers: Agent-Based Simulation Framework for Assessing Their Performance , 2018 .
[19] Minglu Li,et al. SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations , 2015, KDD.
[20] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[21] Zhaohui Wu,et al. Prediction of urban human mobility using large-scale taxi traces and its applications , 2012, Frontiers of Computer Science.
[22] João Gama,et al. Predicting Taxi–Passenger Demand Using Streaming Data , 2013, IEEE Transactions on Intelligent Transportation Systems.
[23] João Mendes-Moreira,et al. Concept Neurons - Handling Drift Issues for Real-Time Industrial Data Mining , 2016, ECML/PKDD.
[24] João Gama,et al. A survey on concept drift adaptation , 2014, ACM Comput. Surv..