Comprehensive evaluation of emergency response capability of urban subway terrorist attacks

doi:10.16265/j.cnki.issn1003-3033.2023.07.2285

Abstract

Abstract:

In order to scientifically evaluate the emergency response capability level of urban subway facing terrorist attacks and improve the construction of urban subway emergency response system, a comprehensive evaluation method of the cloud model for the emergency response capability of urban subway terrorist attacks based on two tuples linguistic DEMATEL-SEWM was established considering the relevance of emergency capacity indicators and the fuzziness and randomness in the evaluation process should as a whole. First of all, the evaluation indicator system of urban subway terrorist attacks emergency response capability was established from the perspective of the whole process equilibrium of emergency management. Furthermore, the weight coefficient of the evaluation indicators was calculated by using two tuples linguistic DEMATEL and SEWM to reflect the correlation between evaluation indicators and the influence of expert judgment difference on weight objectively. Finally, the emergency capability evaluation level was determined by combining the fuzzy proximity method and evaluation cloud map based on the cloud digital eigenvalues obtained by computing the evaluation indicator using the cloud model algorithm. The method was applied to comprehensively evaluate the emergency response capability of the subway terrorist attacks in Q city. The results show that the evaluation level of emergency capacity of the subway in Q city tended to be high, and the evaluation results were basically consistent with the actual survey results, which verified the scientific rationality of the evaluation indicator system and the method, which could provide a theoretical reference.

Key words: urban subway, terrorist attacks, emergency capability evaluation, two tuple linguistic, decision making trial and evaluation laboratory (DEMATEL), structural entropy weight method (SEWM), cloud model

WEI Lin, LI Lihua, QIN Liqiang, XIAO Yanhui, TANG Yuguang. Comprehensive evaluation of emergency response capability of urban subway terrorist attacks[J]. China Safety Science Journal, 2023, 33(7): 213-221.

Figures/Tables 9

Tab.1

Factors and evaluation indicator

因子名称	特征值	方差贡献率/%	累计方差贡献率/%	评价指标	因子载荷	评价指标	因子载荷	评价指标	因子载荷	评价指标	因子载荷
应急预防与准备能力 B₁	8.785	32.712	32.712	反恐预案编制 $C 11$	0.84	反恐法治建设 $C 12$	0.79	专业队伍建设 $C 13$	0.68	反恐科技应用 $C 14$	0.71
				安全设施建设 $C 15$	0.82	反恐培训与演练 $C 16$	0.73	反恐资金投入 $C 17$	0.77	救援物资准备 $C 18$	0.69
				城市化水平 $C 19$	0.74	乘客安全宣传 $C 110$	0.62	—	—	—	—
监测与预警能力 B₂	5.851	18.063	50.775	应急情报信息监测 $C 21$	0.82	危险源识别与分析 $C 22$	0.78	预警信息收集、处理与发布 $C 23$	0.75	—	—
应急响应能力 B₃	3.642	13.252	64.027	恐袭危险报警 $C 31$	0.81	危险等级认定 $C 32$	0.72	现场信息报送 $C 33$	0.74	网络舆情引导 $C 34$	0.68
				现场应急决策 $C 35$	0.77	现场沟通协调 $C 36$	0.67	应急资源调度 $C 37$	0.78	反恐现场处置 $C 38$	0.74
				后勤支援管理 $C 39$	0.64	应急联动速率 $C 310$	0.71	社会紧急救援 $C 311$	0.72	应急通讯保障 $C 312$	0.67
				公众应急意识 $C 313$	0.69	公众应急能力 $C 314$	0.70	—	—	—	—
应急恢复与学习能力 B₄	1.688	6.148	70.175	事件现场清理 $C 41$	0.80	地铁恢复运营 $C 42$	0.73	反恐设施重建 $C 43$	0.75	事件损失评价 $C 44$	0.76
应急恢复与学习能力 B₄	1.688	6.148	70.175	生命财产保障 $C 45$	0.65	恐袭事件调查 $C 46$	0.78	反恐预案修订 $C 47$	0.73	经验知识总结 $C 48$	0.69

Tab.1

Fig.1

Fig.2

Tab.2

Tab.3

Centrality of evaluation indicators for emergency capability evaluation of Q city subway terrorist attacks

评价指标	中心度	排序	评价指标	中心度	排序	评价指标	中心度	排序	评价指标	中心度	排序
$C 11$	3.27	4	$C 110$	1.34	17	$C 36$	0.67	24	$C 41$	1.90	12
$C 12$	2.53	9	$C 21$	3.81	2	$C 37$	0.67	24	$C 42$	1.66	13
$C 13$	3.10	5	$C 22$	3.81	2	$C 38$	0.96	21	$C 43$	0.73	22
$C 14$	2.17	11	$C 23$	7.58	1	$C 39$	0.33	27	$C 44$	0.32	26
$C 15$	3.09	6	$C 31$	1.59	15	$C 310$	0.11	29	$C 45$	1.60	14
$C 16$	3.34	3	$C 32$	1.01	20	$C 311$	1.54	16	$C 46$	0.78	23
$C 17$	3.34	3	$C 33$	2.27	10	$C 312$	1.20	18	$C 47$	0.64	25
$C 18$	3.08	7	$C 34$	2.87	8	$C 313$	0.33	28	$C 48$	1.12	19
$C 19$	3.08	7	$C 35$	0.67	24	$C 314$	0.33	28

Tab.3

Tab.4

Mixed weights and cloud model calculation results of emergency capability evaluation of Q city subway terrorist attacks

综合评价云	$B m$	$W (B m)$	一级指标云数字特征值	C_ij	$W (1)$	$W (2)$	W	二级指标云数字特征值
E_x=3.750 8 E_n=0.384 9 H_e=0.029 8	B₁	0.364 9	(3.651 9,0.369 8,0.023 9)	C₁₁	0.048 9	0.048	0.048 45	(3.84 0,0.586 6,0.020 8)
				C₁₂	0.037 9	0.018	0.027 95	(3.550,0.213 1,0.015 4)
				C₁₃	0.046 4	0.057	0.051 7	(3.687,0.583 0,0.056 7)
				C₁₄	0.032 5	0.02	0.026 25	(3.02,0.576 5,0.017 2)
				C₁₅	0.046 2	0.021	0.033 6	(3.79,0.210 6,0.012 3)
				C₁₆	0.05	0.048	0.049	(3.62,0.330 9,0.019 6)
				C₁₇	0.0 5	0.017	0.017	(3.775,0.282 0,0.022 9)
				C₁₈	0.046	0.019	0.032 5	(3.585,0.249 4,0.017 7)
				C₁₉	0.046	0.009	0.027 5	(3.620,0.1529,0.011 9)
				C₁₁₀	0.02	0.049	0.034 5	(3.67,0.305 8,0.025 7)
	B₂	0.151 3	(3.840 9,0.379 4,0.024 1)	C₂₁	0.057	0.021	0.039	(3.630,0.188 0,0.011 5)
				C₂₂	0.057	0.031	0.044	(3.845 0,0.456 2,0.016 5)
				C₂₃	0.113 5	0.023	0.068 25	(3.950,0.438 7,0.035 8)
	B₃	0.273 9	(3.721 2,0.357 1,0.024 6)	C₃₁	0.023 8	0.04	0.031 9	(3.620,0.152 9,0.011 9)
				C₃₂	0.015 1	0.029	0.022 05	(4.04,0.361 0,0.018 4)
				C₃₃	0.033 9	0.026	0.029 95	(3.65 0,0.338 4,0.027 9)
				C₃₄	0.043	0.017	0.03	(3.610,0.491 3,0.041 2)
				C₃₅	0.01	0.019	0.014 5	(3.670,0.095 3,0.007 0)
				C₃₆	0.01	0.013	0.011 5	(3.445 0,0.294 5,0.018 9)
				C₃₇	0.01	0.031	0.020 5	(3.640,0.340 9,0.027 8)
				C₃₈	0.014 3	0.015	0.014 65	(3.545,0.418 6,0.021 4)
				C₃₉	0.005	0.03	0.017 5	(4.125 0,0.426 1,0.031 4)
				C₃₁₀	0.001 7	0.012	0.006 85	(3.735 0,0.387 3,0.036 1)
				C₃₁₁	0.023	0.042	0.032 5	(3.510,0.165 4,0.011 4)
				C₃₁₂	0.018	0.024	0.021	(3.755,0.373 5,0.033 8)
				C₃₁₃	0.005	0.012	0.008 5	(3.080,0.250 7,0.012 5)
				C₃₁₄	0.005	0.02	0.012 5	(3.055 0,0.382 3,0.035 3)
	B₄	0.209 9	(3.898 3,0.527 9,0.059 6)	C₄₁	0.028 4	0.019	0.023 7	(3.690 0,0.310 8,0.022 1)
				C₄₂	0.024 8	0.061	0.042 9	(4.230 0,0.945 0,0.134 8)
				C₄₃	0.010 9	0.042	0.026 45	(3.690 0,0.335 9,0.024 6)
				C₄₄	0.004 8	0.023	0.013 9	(3.655 0,0.320 8,0.027 1)
				C₄₅	0.024	0.024	0.024	(4.060 0,0.451 2,0.024 8)
				C₄₆	0.011 6	0.014	0.012 8	(4.275 0,0.470 0,0.026 4)
				C₄₇	0.009 5	0.039	0.0242 5	(3.760 0,0.366 0,0.021 4)
				C₄₈	0.016 8	0.067	0.041 9	(3.640 0,0.185 5,0.021 3)

Tab.4

Tab.5

Similarity evaluation results of first-level emergency capability evaluation indicators of Q city subway terrorist attacks

一级应急能力指标	相似度	应急能力评价等级
一级应急能力指标	相似度	Ⅰ级	Ⅱ级	Ⅲ级	Ⅳ级	Ⅴ级
应急预防与准备能力B₁	$ϑ 1$	1.21×10^-11	3.06×10^-10	3.57×10^-8	8.26×10^-1	3.25×10^-2
监测与预警能力B₂	$ϑ 2$	8.35×10^-13	5.04×10^-12	8.11×10^-11	4.80×10^-1	7.94×10^-3
应急响应能力B₃	$ϑ 3$	4.60×10^-12	7.07×10^-11	4.27×10^-9	7.05×10^-1	4.58×10^-3
应急恢复与学习能力B₄	$ϑ 4$	3.61×10^-13	1.35×10^-12	1.06×10^-11	3.79×10^-1	1.02×10^-2

Tab.5

Fig.3

Tab.6

References 14

[1]	杨博森. 西安地铁恐怖主义突发事件应急能力评价指标体系构建及模糊评价研究[D]. 西安: 西北大学, 2017.
	YANG Bosen. Research on the construction of evaluation index system and fuzzy evaluation of Xi'an metro terrorist emergency capability[D]. Xi'an: Northwest University, 2017.
[2]	卢文刚, 王新竹. 全球恐怖袭击主义风险下城市地铁恐袭事件应急能力评估体系构建研究[J]. 行政科学论坛, 2019(7):41-47.
	LU Wen'gang, WANG Xinzhu. Research on construction of emergency capacity assessment system for urban subway terrorist attack under global terrorism risk[J]. Research of Administration Science, 2019(7):41-47.
[3]	卢文刚, 叶丽娅. 基于风险分析的城市地铁恐怖袭击事件应急能力评价研究[J]. 中国应急救援, 2019(3):22-28.
	LU Wen'gang, YE Liya. Study on the evaluation of emergency response capability of urban subway violent terrorist Incident based on risk analysis[J]. China Emergency Rescue, 2019(3):22-28.
[4]	ZANKER J, SCOTT D, REIJINIER E M. Establishing an operational definition of sarcopenia in Australia and New Zealand: Delphi method based consensus statement[J]. The Journal of Nutrition, Health & Aging, 2019, 23(1):105-110.
[5]	杨天姿, 王铁骊, 彭恒明, 等. 小微企业生产安全事故应急脆弱性评价[J]. 中国安全科学学报, 2021, 31(12):176-183. doi: 10.16265/j.cnki.issn 1003-3033.2021.12.023
	YANG Tianzi, WANG Tieli, PENG Hengming, et al. Evaluation on emergency response vulnerability for work safety accidents in small and micro enterprises[J]. China Safety Science Journal, 2021, 31(12):176-183. doi: 10.16265/j.cnki.issn 1003-3033.2021.12.023
[6]	黄亚江, 李书全, 李益锌, 等. 基于DEMATEL-ISM-ANP的地铁运营安全韧性综合评价[J]. 中国安全科学学报, 2022, 32(6):171-177. doi: 10.16265/j.cnki.issn1003-3033.2022.06.2120
	HUANG Yajiang, LI Shuquan, LI Yixin, et al. Comprehensive evaluation on subway operation safety resilience based on DEMATEL-ISM-ANP[J]. China Safety Science Journal, 2022, 32(6):171-177. doi: 10.16265/j.cnki.issn1003-3033.2022.06.2120
[7]	张海波. 应急管理的全过程均衡:一个新议题[J]. 中国行政管理, 2020(3):123-130.
	ZHANG Haibo. The full process balance of emergency management[J]. Chinese Public Administration, 2020(3):123-130.
[8]	刘继川, 桂蕾. 城市公共安全风险评估与控制对策研究:以武汉市为例[J]. 中国安全科学学报, 2022, 32(1):164-171. doi: 10.16265/j.cnki.issn1003-3033.2022.01.022
	LIU Jichuan, GUI Lei. Urban public safety risk assessment and control measures: a case study on Wuhan city[J]. China Safety Science Journal, 2022, 32(1):164-171. doi: 10.16265/j.cnki.issn1003-3033.2022.01.022
[9]	蔡秋蓉, 叶继红. 城市公共安全韧性治理何以可能:适应性循环模型的视角[J]. 天府新论, 2021(4):118-126.
	CAI Qiurong, YE Jihong. Why resilience governance of urban public security is possible: from the perspective of adaptive cycle model[J]. New Horizons from Tianfu, 2021(4):118-126.
[10]	弓晓敏, 耿秀丽, 孙绍荣. 基于二元语义DEMATEL和DEA的多属性群决策方法[J]. 计算机集成制造系统, 2016, 22(8):1993-2000.
	GONG Xiaomin, GENG Xiuli, SUN Shaorong. Multicriteria group decision making based on 2-tuple linguistic DEMATEL and DEA[J]. Computer Integrated Manufacturing Systems, 2016, 22(8):1993-2000.
[11]	张渺. G1-EW组合赋权云模型下地铁运营安全风险评价[J]. 中国安全科学学报, 2022, 32(6):163-170. doi: 10.16265/j.cnki.issn1003-3033.2022.06.0947
	ZHANG Miao. Risk assessment of metro operation based on G1-EW combination weighting cloud model[J]. China Safety Science Journal, 2022, 32(6) : 163-170. doi: 10.16265/j.cnki.issn1003-3033.2022.06.0947
[12]	戴剑勇, 王雯雯, 黄晓庆. 基于网络云模型的尾矿库溃坝安全评估[J]. 安全与环境学报, 2022, 22(1):1-7.
	DAI Jianyong, WANG Wenwen, HUANG Xiaoqing. Safety assessment of tailings reservoir dam break based on network cloud model[J]. Journal of Safety and Environment, 2022, 22(1):1-7.
[13]	徐选华, 吴迪. 基于改进云模型的语言偏好信息多属性大群体决策方法[J]. 管理工程学报, 2018, 32(1):117-125.
	XU Xuanhua, WU Di. Approach for multi-attribute large group decision-making with linguistic preference information based on improved cloud model[J]. Journal of Industrial Engineering/Engineering Management, 2018, 32(1):117-125.
[14]	龚艳冰, 蒋亚东, 梁雪春. 基于模糊贴近度的正态云模型相似度度量[J]. 系统工程, 2015, 33(9):133-137.
	GONG Yanbing, JIANG Yadong, LIANG Xuechun. Similarity measurement for normal cloud models based on fuzzy similarity measure[J]. Systems Engineering, 2015, 33(9):133-137.

评价标准	应急能力评价等级	评分区间	标准云模型数字特征值
Ⅰ级	低	[0,1]	(0,0.515,0.052 4)
Ⅱ级	较低	(1,2]	(1.545,0.318 3,0.032 4)
Ⅲ级	一般	(2,3]	(2.5,0.196 7,0.02)
Ⅳ级	较高	(3,4]	(3.455,0.318 3,0.032 4)
Ⅴ级	高	(4,5]	(5,0.515,0.052 4)

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