Tianhong Zhao
Orcid: 0000-0002-9290-2049
According to our database1,
Tianhong Zhao
authored at least 11 papers
between 2019 and 2024.
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Bibliography
2024
Deep online recommendations for connected E-taxis by coupling trajectory mining and reinforcement learning.
Int. J. Geogr. Inf. Sci., February, 2024
2023
Incorporating multimodal context information into traffic speed forecasting through graph deep learning.
Int. J. Geogr. Inf. Sci., September, 2023
Sensitivity of measuring the urban form and greenery using street-level imagery: A comparative study of approaches and visual perspectives.
Int. J. Appl. Earth Obs. Geoinformation, August, 2023
Comput. Environ. Urban Syst., 2023
Developing a multiview spatiotemporal model based on deep graph neural networks to predict the travel demand by bus.
Int. J. Geogr. Inf. Sci., 2023
2022
Coupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction.
Comput. Environ. Urban Syst., 2022
IEEE Trans. Intell. Transp. Syst., 2022
Correction: Yang et al. Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong-Hong Kong-Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data. Remote Sens. 2019, 11, 2215.
Remote. Sens., 2022
2021
Proceedings of the SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, 2021
2020
2019
Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong-Hong Kong-Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data.
Remote. Sens., 2019