TY  - JOUR
PY  - 2022//
TI  - Dynamic fire risk indexes for stadiums from perspective of big data
JO  - China safety science journal (CSSJ)
A1  - Lu, Ying
A1  - Zhao, Zhipan
A1  - Jiang, Xuepeng
A1  - Wu, Jindong
A1  - Fan, Xiaopeng
SP  - 155
EP  - 162
VL  - 32
IS  - 4
N2  - In order to solve problems that static indicators are more frequently used in fire risk assessment of stadiums, while dynamic indicators are not clear, and internet of things monitoring data required for dynamic assessment is diverse and complex, characteristics of 48 kinds of internet of things monitoring data such as fire host and fire tank liquid level were analyzed, and a quantifiable dynamic index system was constructed, including fault location percentage of fire hosts and difference between actual and standard liquid level. Then, an data set based on monitoring data of 27 stadiums was established, 48 indicators were screened and optimized using random forest algorithm, and development and optimization of dynamic fire risk assessment indicators were studied. The results show that when the 9-dimensional features with the lowest importance are deleted, mean square error reaches the minimum of 0.05, and optimal dynamic fire risk assessment index system for stadiums is obtained.     ===    为解决体育场馆火灾风险评估多采用静态指标而导致动态指标不明确，且动态评估所需物联网监测数据具有多样性和复杂性的问题，分析消防主机、消防水箱液位等48种物联网监测数据特征，构建消防主机故障点位占比、实际与标准液位差等可量化的动态指标体系；建立27个体育场馆监测数据的指标数据集，运用随机森林算法筛选和优化48个指标，研究动态火灾风险评估指标的构建与优化。结果表明：在删除重要度最低的9维特征时，均方误差达到最低0.05,获得最优的体育场馆动态火灾风险评估指标体系。<p />  <p>Language: en</p>
LA  - en
SN  - 1003-3033
UR  - http://dx.doi.org/10.16265/j.cnki.issn1003-3033.2022.04.023
ID  - ref1
ER  -