Broken-Edge Decision-Making Strategy for COVID-19 over Air Railway Composite Network | Zendy

Hui Sun | Zendy; Yicong Qin | Zendy; Zhicheng Mu | Zendy; Rui Wang | Zendy

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Broken-Edge Decision-Making Strategy for COVID-19 over Air Railway Composite Network

Author(s) -

Hui Sun,

Yicong Qin,

Zhicheng Mu,

Rui Wang

Publication year - 2022

Publication title -

computational intelligence and neuroscience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.605

H-Index - 52

eISSN - 1687-5273

pISSN - 1687-5265

DOI - 10.1155/2022/4149477

Subject(s) - covid-19 , mainland china , civil aviation , computer science , enhanced data rates for gsm evolution , composite number , control (management) , outbreak , aviation , operations research , china , telecommunications , engineering , artificial intelligence , geography , aerospace engineering , virology , medicine , disease , archaeology , pathology , algorithm , infectious disease (medical specialty)

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.

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