Distributed Collaborative Simulation Middleware Based on Reflective Memory Network

Shan, Linzhi; Sun, Hong‐Bo

doi:10.1109/cscwd49262.2021.9437793

Cited by 3 publications

(1 citation statement)

References 5 publications

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“…Studies on the Crowd Intelligence Network Model are obtained from Crowd Science and Engineering, which explores the basic principles and laws of the collective intelligence system [34,35] . Researchers have mapped individuals in the real world into digital space, discussed the mechanisms of information diffusion, and analyzed the multi-information disseminations in the Crowd Network [36,37] .…”

Section: Related Workmentioning

confidence: 99%

COVID-19 Spread Simulation in a Crowd Intelligence Network

Shan

Sun

2022

Int. J. Crowd Sci.

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In this paper, the Crowd Intelligence Network Model is applied to the simulation of epidemic spread. This model combines the multilayer coupling network model and the two-stage feedback member model to study the epidemic spread mechanisms under multiple-scene intervention. First, this paper establishes a multi-layer coupled network structure based on the characteristic of Social Network, Information Network, and Monitor Network, namely, the Crowd Intelligence Network structure. Then, based on this structure, the digital-self model, which has a multiple-scene effect and two-stage feedback structure, is designed. It has an emotional state and infection state quantified by using attitude and self-protection levels. This paper uses the attitude level and selfprotection level to quantify individual emotions and immune levels, and discusses the impact of individual emotions on epidemic prevention and control. Finally, the availability of the Crowd Intelligence Network Model on the epidemic spread is verified by comparing the simulation trend with the actual spread trend of COVID-19.

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