Networks Under Deep Uncertainty

Fuad Aleskerov () and Daniil Tkachev
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Fuad Aleskerov: HSE University
Daniil Tkachev: HSE University

A chapter in Dynamics of Disasters, 2024, pp 1-13 from Springer

Abstract: Abstract The situation of deep uncertainty is defined by the absence of any statistical evaluations of the situation development. For instance, such situations may include events that occur for the first time. We use scenario analysis to model the potential outcomes of events affecting networks under deep uncertainty. Centrality indices are used to identify vulnerable vertices in networks. We consider classic and new centrality indices. The new centrality indices take into account the properties of vertices and group influence. We have constructed a network of export/import and production data of basic crops (rice, wheat, maize, sorghum, barley, rye, millet, buckwheat, oats), as well as oil and rare earth compound trade for 2020. We have considered scenarios of various situations and identified the most vulnerable countries in these scenarios.

Date: 2024
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DOI: 10.1007/978-3-031-74006-0_1

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