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Nonlinear and Synergistic Effects of Station-area Built Environments on Metro Ridership: A Shapley Additive Explanations (SHAP) Analysis
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Yufei WANG1, Haosen YANG2, Bingjie YU2, Fei FU2, Linchuan YANG2
Urban Rapid Rail Transit | 2024, 37(2) : 1 - 7
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Urban Rapid Rail Transit | 2024, 37(2): 1-7
• Forum of Rapid Rail Transit •
Nonlinear and Synergistic Effects of Station-area Built Environments on Metro Ridership: A Shapley Additive Explanations (SHAP) Analysis
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Yufei WANG1, Haosen YANG2, Bingjie YU2, Fei FU2, Linchuan YANG2
Affiliations
  • 1 School of Economics and Management University of Electronic Science and Technology of China Chengdu 611731
  • 2 School of Architecture Southwest Jiaotong University Chengdu 611756
doi: 10.3969/j.issn.1672-6073.2024.02.001
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This study uses multisource big data (e.g., metro card transactions, mobile phone signaling, and points of interest (POIs)) and interpretable machine learning methods (integrating random forest and Shapley additive explanations (SHAP) models) to investigate the nonlinear relationship between stationarea built environments and Chengdu Metro ridership as well as the synergistic effects among built environment variables. The results indicate that the three most important built environment determinants of metro ridership are the floor area ratio, employment density, and road density. Moreover, the SHAP model results reveal the threshold and synergistic effects of the stationarea built environment variables on metro ridership. These findings provide theoretical support and policy insights for transitoriented developmental (TOD) planning and practice.

urban rail transit  /  transit-oriented development (TOD)  /  built environment  /  synergistic effect  /  nonlinearity  /  machine learning
汪雨菲, 杨皓森, 喻冰洁, 付飞, 杨林川. 站域建成环境与地铁客流量的非线性关系和协同效应-可解释机器学习分析. 都市快轨交通, 2024 , 37 (2) : 1 -7 . DOI: 10.3969/j.issn.1672-6073.2024.02.001
Yufei WANG, Haosen YANG, Bingjie YU, Fei FU, Linchuan YANG. Nonlinear and Synergistic Effects of Station-area Built Environments on Metro Ridership: A Shapley Additive Explanations (SHAP) Analysis[J]. Urban Rapid Rail Transit, 2024 , 37 (2) : 1 -7 . DOI: 10.3969/j.issn.1672-6073.2024.02.001
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Year 2024 volume 37 Issue 2
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Article Info
doi: 10.3969/j.issn.1672-6073.2024.02.001
  • Receive Date：2023-10-20
  • Online Date：2025-07-09
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  • Received：2023-10-20
  • Revised：2023-12-13
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Affiliations
    1 School of Economics and Management University of Electronic Science and Technology of China Chengdu 611731
    2 School of Architecture Southwest Jiaotong University Chengdu 611756
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表12种不同金属材料的力学参数
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Family		 属数
Number of
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Number of
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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