The following publications are possibly variants of this publication:
- Interpreting core forms of urban morphology linked to urban functions with explainable graph neural networkDongsheng Chen, Yu Feng 0006, Xun Li, Mingya Qu, Peng Luo, Liqiu Meng. urban, 118:102267, 2025. [doi]
- Unraveling nonlinear and spatial non-stationary effects of urban form on surface urban heat islands using explainable spatial machine learningYujia Ming, Yong Liu, Yingpeng Li, Yongze Song. urban, 114:102200, 2024. [doi]
- Spatio-temporal graph convolutional networks for road network inundation status prediction during urban floodingFaxi Yuan, Yuanchang Xu, Qingchun Li, Ali Mostafavi. urban, 97:101870, 2022. [doi]
- Spatiotemporal evolution analysis of time-series land use change using self-organizing map to examine the zoning and scale effectsJianchao Qi, Huiping Liu, Xiangping Liu, Yanghua Zhang. urban, 76:11-23, 2019. [doi]
- Extracting spatial effects from machine learning model using local interpretation method: An example of SHAP and XGBoostZiqi Li. urban, 96:101845, 2022. [doi]
- Identifying borders of activity spaces and quantifying border effects on intra-urban travel through spatial interaction networkMeihan Jin, Lunsheng Gong, Yanqin Cao, Pengcheng Zhang, Yongxi Gong, Yu Liu 0003. urban, 87:101625, 2021. [doi]
- Soft computing model based financial aware spatiotemporal social network analysis and visualization for smart citiesLei Ruan, Chunyan Li, Yan Zhang, Haoxiang Wang. urban, 77, 2019. [doi]