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The Impact of Machine Learning-based Community Built Environment on Walking Time of the Elderly
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Zhen-jun ZHU1, Zhan-peng HE1, Jia-wen YU2, Ji HAN1, Qing LI1
Science Technology and Engineering | 2025, 25(18) : 7832 - 7842
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Science Technology and Engineering | 2025, 25(18): 7832-7842
• Papers·Traffics and Transportations •
The Impact of Machine Learning-based Community Built Environment on Walking Time of the Elderly
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Zhen-jun ZHU1, Zhan-peng HE1, Jia-wen YU2, Ji HAN1, Qing LI1
Affiliations
  • 1 College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
  • 2 School of Transportation, Southeast University, Nanjing 211189, China
Published: 2025-06-28 doi: 10.12404/j.issn.1671-1815.2405699
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To explore the impact of the community built environment on the walking time of elderly people, and considering gender differences among the elderly group, a CatBoost model was constructed and the SHAP (Shapley additive explanations) explanation method was integrated. The relative importance and nonlinear relationships of the community built environment features with the walking time of elderly people of different genders were comparatively analyzed. The study findings indicate that the community built environment variables have a more significant influence on the walking time of the elderly compared to personal socioeconomic attributes. However, the impact varies between genders. Compared to elderly males, elderly females pay more attention to built environment variables closely related to social needs, such as NDVI and population density. In contrast, the walking time of elderly males is more closely associated with personal socioeconomic attributes, often linked to transportation convenience and travel efficiency.

community built environment  /  elderly people  /  walking time  /  CatBoost model  /  SHAP explanation method
Zhen-jun ZHU, Zhan-peng HE, Jia-wen YU, Ji HAN, Qing LI. The Impact of Machine Learning-based Community Built Environment on Walking Time of the Elderly[J]. Science Technology and Engineering, 2025 , 25 (18) : 7832 -7842 . DOI: 10.12404/j.issn.1671-1815.2405699
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Year 2025 volume 25 Issue 18
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Article Info
doi: 10.12404/j.issn.1671-1815.2405699
  • Receive Date：2024-07-29
  • Online Date：2025-12-17
  • Published：2025-06-28
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  • Received：2024-07-29
  • Revised：2025-03-28
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    1 College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
    2 School of Transportation, Southeast University, Nanjing 211189, China
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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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