Electrical fire risk assessment of high-rise buildings based on hybrid decision model considering asymmetric proximity

被引:4
作者
Su, Lei [1 ]
Yang, Fan [1 ]
Shen, Yu [1 ]
Yang, Zhichun [1 ]
机构
[1] State Grid Hubei Elect Power Res Inst, Wuhan, Hubei, Peoples R China
关键词
association rules; asymmetric closeness; cloud theory; electrical fire; high-rise building; SYSTEM;
D O I
10.1002/fam.3096
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
At present, there are some problems in the research of electrical fire risk assessment of high-rise buildings, such as the evaluation index is relatively single and the fuzziness of evaluation state boundary is not considered. This study proposed an electrical fire risk assessment method of high-rise buildings based on hybrid decision model considering asymmetric proximity. Based on the occurrence mechanism of electrical fire in high-rise buildings, a four-level evaluation index system considering disaster causing body, fire site environment, affected body and fire driving factors is established based on FP growth (Frequent Pattern Tree Growth) mining association rules, and the risk grade is divided further. An improved index weight assignment method for balancing the interaction relationship between indexes is proposed, and a hybrid decision-making model for electrical fire risk assessment of high-rise buildings is established. Combined with specific examples, the effectiveness of the proposed building electrical fire risk assessment method is verified. The weight standard deviation of the proposed method is 0.0464, which is about 13.8% smaller than that of analytic hierarchy process (0.0528). So the method can better balance each risk evaluation index, fully consider the fuzziness and randomness in the electrical fire risk assessment of high-rise buildings, and improve the accuracy and applicability of electrical fire risk assessment.
引用
收藏
页码:285 / 293
页数:9
相关论文
共 20 条
  • [11] Lu QY., 2018, 2018 2 IEEE C ENERGY
  • [12] Matos AC, 2018, OCCUPATIONAL SAFETY AND HYGIENE VI, P401
  • [13] Applying the Distribution System in Grid Restoration/NERC CIP-014 Risk Assessment
    Mukherjee, Srijib
    [J]. 2015 IEEE RURAL ELECTRIC POWER CONFERENCE (REPC), 2015, : 103 - 105
  • [14] Nugroho Paulus Setyo, 2020, APCORISE 2020: Proceedings of the 3rd Asia Pacific Conference on Research in Industrial and Systems Engineering 2020, P247, DOI 10.1145/3400934.3400980
  • [15] Qingchun Kang, 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2010), P1349, DOI 10.1109/FSKD.2010.5569095
  • [16] Design of Multi-Information Fusion Based Intelligent Electrical Fire Detection System for Green Buildings
    Ren, Xiaogeng
    Li, Chunwang
    Ma, Xiaojun
    Chen, Fuxiang
    Wang, Haoyu
    Sharma, Ashutosh
    Gaba, Gurjot Singh
    Masud, Mehedi
    [J]. SUSTAINABILITY, 2021, 13 (06)
  • [17] Probabilistic Risk Assessment of an Active Distribution Network Using Monte Carlo Simulation Approach
    Shahzad, Umair
    Asgarpoor, Sohrab
    [J]. 2019 51ST NORTH AMERICAN POWER SYMPOSIUM (NAPS), 2019,
  • [18] Singh A., 2011, 2011 International Conference on Recent Trends in Information Systems (ReTIS), P126, DOI 10.1109/ReTIS.2011.6146853
  • [19] Ying Li, 2019, 2019 IEEE 11th International Conference on Advanced Infocomm Technology (ICAIT), P179, DOI 10.1109/ICAIT.2019.8935933
  • [20] Yuanchun Ding, 2011, Proceedings of the 2011 3rd International Conference on Advanced Computer Control (ICACC 2011), P265, DOI 10.1109/ICACC.2011.6016411