Research Article
Stochastic Risk Assessment with a Lagrangian Solution for the Optimal Cost Allocation in High-Speed Rail Networks
Table 2
Station indexes and impact.
| No. | Name | Station class | Degree | Degree centrality | Betweenness centrality | Station scale | Impact (H) |
| 1 | Si’an | 2 | 1 | 0.042 | 0 | 0.750 | 0.233 | 2 | Chengchow | 2 | 3 | 0.125 | 0.217 | 0.750 | 0.359 | 3 | Shangqiu | 4 | 2 | 0.083 | 0.188 | 0.250 | 0.186 | 4 | Hsuchow | 3 | 2 | 0.083 | 0.246 | 0.500 | 0.290 | 5 | Huainan | 4 | 2 | 0.083 | 0.174 | 0.250 | 0.179 | 6 | Bengbu | 3 | 3 | 0.125 | 0.406 | 0.500 | 0.378 | 7 | Xinyang | 4 | 2 | 0.083 | 0.159 | 0.250 | 0.171 | 8 | Ho-fei | 2 | 4 | 0.167 | 0.543 | 0.750 | 0.530 | 9 | Nanking | 2 | 4 | 0.167 | 0.623 | 0.750 | 0.570 | 10 | Chinkiang | 4 | 2 | 0.083 | 0.188 | 0.250 | 0.186 | 11 | Soochow | 2 | 2 | 0.083 | 0.094 | 0.750 | 0.289 | 12 | Yueyang | 4 | 2 | 0.083 | 0.275 | 0.250 | 0.229 | 13 | Wuhan | 2 | 4 | 0.167 | 0.565 | 0.750 | 0.541 | 14 | Chaohu | 3 | 2 | 0.083 | 0.072 | 0.500 | 0.203 | 15 | Huzhou | 4 | 2 | 0.083 | 0.312 | 0.250 | 0.247 | 16 | Shanghai | 1 | 2 | 0.083 | 0.058 | 1 | 0.346 | 17 | Changsha | 2 | 3 | 0.125 | 0.261 | 0.750 | 0.380 | 18 | Nanchang | 2 | 3 | 0.125 | 0.152 | 0.750 | 0.326 | 19 | Shangrao | 3 | 4 | 0.167 | 0.217 | 0.500 | 0.292 | 20 | Hangzhou | 2 | 4 | 0.167 | 0.449 | 0.750 | 0.483 | 21 | Ningbo | 3 | 2 | 0.083 | 0.217 | 0.500 | 0.275 | 22 | Kwangchow | 2 | 2 | 0.083 | 0.109 | 0.750 | 0.296 | 23 | Shamchun | 2 | 2 | 0.083 | 0.022 | 0.750 | 0.253 | 24 | Hockchew | 2 | 3 | 0.125 | 0.065 | 0.750 | 0.283 | 25 | Yujeu | 3 | 2 | 0.083 | 0.094 | 0.500 | 0.214 |
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