
Estimating real-time mobility flows between OD pairs with different ranges of scaling factors β.
Related publications:
Huang, Z., Mireles de Villafranca, A.E. and Sipetas, C., 2022. Sensing Multi-modal Mobility Patterns: A Case Study of Helsinki using Bluetooth Beacons and a Mobile Application. arXiv preprint arXiv:2209.13537. IEEE BigData 2022, to appear.
Heydari, S., Huang, Z., Hiraoka T., Ponce de León Chávez, A., Ala-Nissilä T., Leskelä, L., Kivelä M. and Saramäki J., 2022. Estimating inter-regional mobility during disruption: comparing and combining different data sources. Travel Behav. Soc. 31, 93-105.
Huang, Z., Ling, X., Wang, P., Zhang, F., Mao, Y., Lin, T., Wang, F., 2018. Modeling real-time human mobility based on mobile phone and transportation data fusion. Transp. Res. Part C Emerg. Technol. 96, 251–269.
Huang, Z., Wang, P., Zhang, F., Gao, J., Schich, M., 2018. A mobility network approach to identify and anticipate large crowd gatherings. Transp. Res. Part B Methodol. 114, 147–170.