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Decision-support model for safety evaluation of existing civil buildings and its application
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Mengfan DAI1, Lingzhi LI**, 1, Yuxin QIAN2, Jingfeng YUAN3, Xiaojian HAN1, Changhao ZHAO1
China Safety Science Journal | 2025, 35(9) : 193 - 201
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China Safety Science Journal | 2025, 35(9): 193-201
• Safety engineering technology •
Decision-support model for safety evaluation of existing civil buildings and its application
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Mengfan DAI1, Lingzhi LI**, 1, Yuxin QIAN2, Jingfeng YUAN3, Xiaojian HAN1, Changhao ZHAO1
Affiliations
  • 1College of Civil Engineering, Nanjing Tech University, Nanjing Jiangsu 211816, China
  • 2School of Computer Science and Technology (School of Artificial Intelligence), Nanjing Tech University, Nanjing Jiangsu 211816, China
  • 3School of Civil Engineering, Southeast University, Nanjing Jiangsu 211189, China
Published: 2025-09-28 doi: 10.16265/j.cnki.issn1003-3033.2025.09.1527
Outline
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To improve the efficiency of safety inspections for existing civil buildings, this study develops a decision-support model for safety evaluation of existing civil buildings based on ML techniques. Building safety feature data were first collected from building evaluation reports. Then, a multi-dimensional indicator system integrating "design-evolution-status" features was established through correlation analysis and recursive feature elimination with cross-validation. Subsequently, five ML models were built and evaluated using performance metrics such as accuracy, precision, and recall. Furthermore, a decision-support platform for safety evaluation of existing civil buildings was developed and validated through a real engineering project to examine its practical operability. The results demonstrate that, compared to design features, evolution and status features more effectively reflect the actual safety conditions of civil buildings. In particular, building age, renovation or extension history, and concrete beam load capacity are identified as key features. Among the tested models, the Decision Tree algorithm shows the best performance in evaluating the safety of enclosure system, superstructure, foundation, and individual evaluation unit.

machine learning (ML)  /  existing civil buildings  /  safety evaluation  /  decision-support model  /  indicator system
戴梦璠, 李灵芝副教授, 钱宇昕, 袁竞峰教授, 韩晓健教授, 赵昌皓. 既有民用建筑安全鉴定辅助决策模型及应用. 中国安全科学学报, 2025 , 35 (9) : 193 -201 . DOI: 10.16265/j.cnki.issn1003-3033.2025.09.1527
Mengfan DAI, Lingzhi LI, Yuxin QIAN, Jingfeng YUAN, Xiaojian HAN, Changhao ZHAO. Decision-support model for safety evaluation of existing civil buildings and its application[J]. China Safety Science Journal, 2025 , 35 (9) : 193 -201 . DOI: 10.16265/j.cnki.issn1003-3033.2025.09.1527
Year 2025 volume 35 Issue 9
298
69
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2025.09.1527
  • Receive Date:2025-04-08
  • Online Date:2026-07-09
  • Published:2025-09-28
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  • Received:2025-04-08
  • Revised:2025-06-30
Funding
Affiliations
    1College of Civil Engineering, Nanjing Tech University, Nanjing Jiangsu 211816, China
    2School of Computer Science and Technology (School of Artificial Intelligence), Nanjing Tech University, Nanjing Jiangsu 211816, China
    3School of Civil Engineering, Southeast University, Nanjing Jiangsu 211189, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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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