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A Two-Steps Dynamic Demand Estimation Approach Sequentially Adjusting Generations and Distributions., , , and . ITSC, page 1477-1482. IEEE, (2015)Using Passive Data Collection Methods to Learn Complex Mobility Patterns: An Exploratory Analysis., , , and . ITSC, page 993-998. IEEE, (2018)Long-term & short-term bike sharing demand predictions using contextual data., , and . MT-ITS, page 1-6. IEEE, (2023)A Markov chain dynamic model for trip generation and distribution based on CDR., , and . MT-ITS, page 243-250. IEEE, (2015)Mobility-Driven and Energy-Efficient Deployment of Edge Data Centers in Urban Environments., , , , and . IEEE Trans. Sustain. Comput., 7 (4): 736-748 (2022)A low dimensional model for bike sharing demand forecasting., , and . MT-ITS, page 1-7. IEEE, (2019)Assessing the consistency between observed and modelled route choices through GPS data., , , and . MT-ITS, page 216-222. IEEE, (2015)Effectiveness of the two-step dynamic demand estimation model on large networks., , and . MT-ITS, page 356-361. IEEE, (2017)The Impact of Route Choice Modeling on Dynamic OD Estimation., , , , and . ITSC, page 1483-1488. IEEE, (2015)Leveraging GIS Data and Topological Information to Infer Trip Chaining Behaviour at Macroscopic Level., , , and . MT-ITS, page 1-10. IEEE, (2019)