A Granular Functional Network with delay: Some dynamical properties and application to the sign prediction in social networks

Loia, Vincenzo; Parente, Mimmo; Pedrycz, Witold; Tomasiello, Stefania

doi:10.1016/j.neucom.2018.08.047

Cited by 17 publications

(1 citation statement)

References 33 publications

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“…A more in-depth study on how to derive CA(u, t) and, thus, the weights for the determination of α and β is underway. We are investigating two directions: the adoption of more complex operators, such as Ordered Weighted Averaging (OWA) operators [24], to aggregate Google data and uses fuzzy cognitive maps [25] and granular functional networks [26] to consider the effects of retention measures in greater detail.…”

Section: Discussionmentioning

confidence: 99%

A method based on Graph Theory and Three Way Decisions to evaluate critical regions in epidemic diffusion:

2021

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The paper reports the results of an analysis of COVID-19 diffusion in Italy. The analysis was carried out with a new method based on the combined use of a 3 Way Decisions model and graph theory. Specifically, the data about infected people in the Italian regions is assessed by means of an evaluation function which allows the tri-partitioning of Italy and the identification of high, medium or low critical regions. The tri-partition is performed, along the temporal evolution of the COVID-19 diffusion, by calculating two threshold values which take into account the containment actions that, from time to time, the decision makers have implemented. The effects of a containment action are related to a reduction in the centrality value of a region. To estimate the effect of containment actions, we evaluated two approaches. The first is based on a uniform reduction in the centrality values of the regions, the second estimates the effects of containment actions starting from the mobility changes data provided by the Google Community Mobility reports. The results of our evaluation based on real data of the COVID-19 diffusion in Italy are encouraging and represent a good starting point for future extensions of the method.

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Section: Discussionmentioning

confidence: 99%