Name
Abstract | ||
|---|---|---|
In order to control the spread of the COVID-19 virus, this study proposes an ARCN-SUTS (air railway composite network susceptible-untested-tested-susceptible) model based on the correlation characteristics of the air railway composite network in mainland China. Furthermore, this study also puts forward a broken-edge decision-making strategy for the purpose of making decision about the edge efficiently broken and avoiding the second outbreak of the virus spread to minimize the economic losses for railway and civil aviation companies. Finally, simulation results demonstrate that the proposed strategy can effectively control the spread of the virus with minimal economic losses. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1155/2022/4149477 | COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE |
DocType | Volume | ISSN |
Journal | 2022 | 1687-5265 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Sun | 1 | 0 | 0.68 |
| Yicong Qin | 2 | 0 | 0.68 |
| Zhicheng Mu | 3 | 0 | 0.34 |
| Rui Wang | 4 | 0 | 0.34 |