Network resistance analysis and key nodes identification of subway distribution network under road-rail coordination

doi:10.16265/j.cnki.issn1003-3033.2024.10.1659

Abstract

Abstract:

In order to study the invulnerability and key nodes of the metro network in road-rail cooperative urban distribution, so as to support the networking mode of urban distribution and the reliability improvement of the distribution network under road-rail cooperation, the relative network efficiency and relative load entropy were used as the invulnerability measurement indicators, and the network invulnerability changes under different attack modes were studied based on the improved coupling image lattice model first. Secondly, the centrality index of the transportation efficiency of the reaction network and the realistic index of the carrying capacity of the reaction network was selected to construct a comprehensive identification model of key nodes of the network. Then, by analyzing the level of network invulnerability under different index weights, the key node set under the optimal weight value was obtained. Finally, the empirical analysis of the Chengdu metro network was carried out to verify the effectiveness and practicability of the model. The results show that the metro network has a stronger anti-destruction ability in the face of random attacks under the same disturbance intensity. When faced with external disturbances, the relative network efficiency and relative load entropy loss of nodes with a loss of more than 20% is 6.3% and 6.8%, respectively, of which the relative network efficiency loss can reach 56.3%, and the relative load entropy loss can reach 50.2%. Considering the realistic and central indicators, the relative network efficiency loss and the maximum relative load entropy loss caused by each key node are 8.99% and 4.38%, respectively, which need to be paid attention to.

Key words: road-rail coordination, metro distribution network, resistance to destruction, key nodes, coupling image lattice(CML)models, cascade failure

CLC Number:

X913.4安全系统工程

ZHANG Jin, CHEN Lang, SHEN Hao, LI Guoqi. Network resistance analysis and key nodes identification of subway distribution network under road-rail coordination[J]. China Safety Science Journal, 2024, 34(10): 39-49.

Figures/Tables 16

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Table 1

Fig.7

Fig.8

Fig.9

Table 2

Impact of each node failure on the resistance of the network

站点编号	站点	综合排序	$V 1$ 损失/%	$V 2$ 损失/%
181	高升桥	1	56.3	50.2
259	花牌坊	2	52.2	48.6
236	中坝	3	48.0	41.8
324	梓潼宫	4	42.2	40.4
173	红牌楼	5	38.8	39.6
244	抚琴	6	38.1	39.5
61	观东	7	31.0	28.2
59	华府大道	8	31.1	25.7
325	皇花园	9	31.4	24.5
106	金石路	10	27.1	24.4
146	东湖公园	11	23.7	20.4
108	航都大街	12	0.9	39.2
276	府青路	13	21.2	16.3
56	新通大道	14	1.5	35.9
121	华兴	15	23.1	7.8

Table 2

Fig.10

Fig.11

Table 3

Average invulnerability measure of key nodes under different coefficients

系数取值		考虑因素	关键节点平均测度
$θ 1$	$θ 2$	考虑因素	相对网络效率	相对负载熵
0	1	仅考虑现实性指标	0.915 6	0.960 4
1	0	仅考虑中心性指标	0.911 6	0.964 0
0.6	0.4	同时考虑,且网络连通性影响最大	0.910 1	0.965 3
0.5	0.5	同时考虑,且负载稳定性影响最大	0.912 3	0.956 2

Table 3

Table 4

Fig.12

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排名	基于节点度的排名		基于节点介数的排名		基于节点强度的排名
排名	取值	站点	取值	站点	取值	站点
1	6	东光	0.242	孵化园	853 128	市二医院
2	6	孵化园	0.201	中医大省医院	705 103	骡马市
3	6	省体育馆	0.175	锦城大道	670 483	玉双路
4	6	双桥路	0.168	华兴	629 284	太升南路
5	6	市二医院	0.165	省体育馆	581 101	春熙路

偏重网络连通性识别的关键节点				偏重负载稳定性识别的关键节点
站点名称 (节点编号)	重要度排序	站点名称 (节点编号)	重要度排序	站点名称 (节点编号)	重要度排序	站点名称 (节点编号)	重要度排序
孵化园(90)	1	世纪城(76)	14	孵化园(90)	1	文化宫(231)	14
华兴(121)	2	神仙树(139)	15	华兴(121)	2	世纪城(76)	15
火车南站(130)	3	三元(97)	16	火车南站(130)	3	前锋路(250)	16
高朋大道(144)	4	金融城(101)	17	高朋大道(144)	4	人民北路(263)	17
太平园(158)	5	前锋路(250)	18	太平园(158)	5	三元(97)	18
中医大省医院(221)	6	人民北路(263)	19	中医大省医院(221)	6	金融城(101)	19
春熙路(202)	7	成都西站(260)	20	春熙路(202)	7	凤溪河(266)	20
一品天下(271)	8	海昌路(42)	21	一品天下(271)	8	成都西站(260)	21
省体育馆(171)	9	高升桥(181)	22	省体育馆(171)	9	火车北站(281)	22
武青南路(152)	10	驷马桥(280)	23	武青南路(152)	10	东光(147)	23
锦城大道(87)	11	火车北站(281)	24	市二医院(209)	11	海昌路(42)	24
文化宫(231)	12	琉璃场(133)	25	神仙树(139)	12	高升桥(181)	25
市二医院(209)	13			锦城大道(87)	13