Mingxiao Li
Mingxiao Li
Shenzhen University
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Multiscale dynamic human mobility flow dataset in the US during the COVID-19 epidemic
Y Kang, S Gao, Y Liang, M Li, J Rao, J Kruse
Scientific data 7 (1), 390, 2020
A ST-CRF map-matching method for low-frequency floating car data
X Liu, K Liu, M Li, F Lu
IEEE Transactions on Intelligent Transportation Systems 18 (5), 1241-1254, 2016
Reconstruction of human movement trajectories from large-scale low-frequency mobile phone data
M Li, S Gao, F Lu, H Zhang
Computers, Environment and Urban Systems 77, 101346, 2019
Fine-grained prediction of urban population using mobile phone location data
J Chen, T Pei, SL Shaw, F Lu, M Li, S Cheng, X Liu, H Zhang
International Journal of Geographical Information Science 32 (9), 1770-1786, 2018
Predicting future locations of moving objects with deep fuzzy-LSTM networks
M Li, F Lu, H Zhang, J Chen
Transportmetrica A: Transport Science 16 (1), 119-136, 2020
Prediction of human activity intensity using the interactions in physical and social spaces through graph convolutional networks
M Li, S Gao, F Lu, K Liu, H Zhang, W Tu
International Journal of Geographical Information Science 35 (12), 2489-2516, 2021
Predicting the spatiotemporal legality of on-street parking using open data and machine learning
S Gao, M Li, Y Liang, J Marks, Y Kang, M Li
Annals of GIS 25 (4), 299-312, 2019
Coupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction
T Zhao, Z Huang, W Tu, B He, R Cao, J Cao, M Li
Computers, Environment and Urban Systems 94, 101776, 2022
Dynamic estimation of individual exposure levels to air pollution using trajectories reconstructed from mobile phone data
M Li, S Gao, F Lu, H Tong, H Zhang
International journal of environmental research and public health 16 (22), 4522, 2019
A privacy‐preserving framework for location recommendation using decentralized collaborative machine learning
J Rao, S Gao, M Li, Q Huang
Transactions in GIS 25 (3), 1153-1175, 2021
Predicting future locations with deep fuzzy-LSTM network
LI Mingxiao, Z Hengcai, QIU Peiyuan, C Shifen, C Jie, LU Feng
Acta Geodaetica et Cartographica Sinica 47 (12), 1660, 2018
Automatic urban road network extraction from massive GPS trajectories of taxis
S Gao, M Li, J Rao, G Mai, T Prestby, J Marks, Y Hu
Handbook of Big Geospatial Data, 261-283, 2021
Relationships between building attributes and COVID-19 infection in London
H Tong, M Li, J Kang
Building and Environment 225, 109581, 2022
Optimization on arrangement of precaution areas serving for ships’ routeing in the Taiwan strait based on massive AIS data
J Chen, F Lu, M Li, P Huang, X Liu, Q Mei
Data Mining and Big Data: First International Conference, DMBD 2016, Bali …, 2016
Using multi-sourced big data to correlate sleep deprivation and road traffic noise: A US county-level ecological study
H Tong, JL Warren, J Kang, M Li
Environmental research 220, 115029, 2023
Fine-grained crowd distribution forecasting with multi-order spatial interactions using mobile phone data
M Li, S Gao, P Qiu, W Tu, F Lu, T Zhao, Q Li
Transportation Research Part C: Emerging Technologies 144, 103908, 2022
An enhanced model for evacuation vulnerability assessment in urban areas
J Chen, T Pei, M Li, C Song, T Ma, F Lu, SL Shaw
Computers, Environment and Urban Systems 84, 101540, 2020
Fine-grained dynamic population mapping method based on large-scale sparse mobile phone data
M Li, H Zhang, J Chen
2019 20th IEEE International Conference on Mobile Data Management (MDM), 473-478, 2019
The near-real-time prediction of urban population distributions based on mobile phone location data
C Lina, WU Sheng, C Jie, LI Mingxiao, LU Feng
Journal of Geo-Information Science 20 (4), 523-531, 2018
A data-driven approach to understanding and predicting the spatiotemporal availability of street parking
M Li, S Gao, Y Liang, J Marks, Y Kang, M Li
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances …, 2019
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