主管：中华人民共和国应急管理部
主办：应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU
消防科学与技术

消防科学与技术 ›› 2021, Vol. 40 ›› Issue (7): 1086-1088.

• • 上一篇    下一篇

城乡火灾风险与社会性指标的关联性研究

张琰1，王哲亮2，张欣1，王占伟3，李晋1   

  1. 1. 应急管理部天津消防研究所，天津300381；2. 河南省消防救援总队，河南郑州450004；3. 北京市消防救援总队，北京100085
  • 出版日期:2021-07-15 发布日期:2021-07-15
  • 作者简介:张琰（1991-），男，河北衡水人，应急管理部天津消防研究所助理研究员，硕士，主要从事消防安全技术和粉尘爆炸相关研究，天津市南开区卫津南路110号，300381。
  • 基金资助:
    应急管理部消防救援局重点攻关项目(2020XFZD01)；应急管理部天津消防研究所基础科研业务费项目(2020SJ03)

The study of correlation analysis between fire risk and social factors

ZHANG Yan1, WANG Zhe-liang2, ZHANG Xin1, WANG Zhan-wei3, LI Jin1   

  1. 1. Tianjin Fire Research Science and Technology Institute of MEM, Tianjin 300381,China; 2. Henan General Fire and Rescue Brigade, Henan Zhengzhou 450004, China; 3. Beijing General Fire and Rescue Brigade, Beijing 100085, China
  • Online:2021-07-15 Published:2021-07-15

摘要： 为探究社会性因素对城乡火灾风险的影响权重，基于火灾历史数据计算GDP、常住人口和受教育程度等指标与城乡火灾风险的关联性。计算分析发现，GDP 总量与火灾数量呈现正相关关系，在省份维度GDP 总量与火灾数量呈现强相关，在城市维度GDP 总量与火灾数量呈现中等相关；各省常住人口与本省火灾数量呈现强相关关系，但经济欠发达省份的关联性较弱；居民受教育程度较低时，教育水平与火灾发生数量呈负相关，高教育阶段时，教育水平与火灾发生数量呈正相关。

关键词: 消防, 火灾风险, 经济指标, 人口指标, 关联分析

Abstract: In order to study the influence of social factors on fire risk, grey correlation analysis method was adopted to calculate the correlation between social indexes, such as GDP, population and education level, and fire risk based on the historical fire data. The study shows GDP was positively correlated with the number of fires.The number of fires in provinces was strongly correlated with GDP, nevertheless the number of fires in cities was moderately correlated with GDP. There was a strong correlation between the resident population and the number of fires in each province, but the correlation was weak in less devloped provinces. The education level was negatively correlated with the number of fires when the education level of residents was low. However, the education level was positively correlated with the number of fires when the education level was high.

Key words: fire risk, economic factors, population factors, correlation analysis