Topic
Network theory
About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.
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TL;DR: The results indicate that right-sided asymmetry of multifractal spectra is linked with the degree of small-worldness present in networks and emerges with the presence of the following topological properties: low edge density, low average shortest path, and high clustering coefficient.
17 citations
TL;DR: A novel correlation centrality index is put forward, which considers the node importance contribution in the whole network adequately to overcome the insufficiencies of the interaction between the adjacent nodes, and a multi-attribute node importance decision making method based on entropy is proposed.
Abstract: In this paper, we firstly put forward a novel correlation centrality index, which considers the node importance contribution in the whole network adequately to overcome the insufficiencies of the interaction between the adjacent nodes. Then, we propose a multi-attribute node importance decision making method based on entropy, which combines the advantages of degree centrality, efficiency centrality, betweenness centrality and correlation centrality, to make up for the one-sidedness of a single index in node importance evaluation. Finally, we demonstrate the accuracy of the correlation centrality index compared with the evaluation matrix method by simulating cascading failures on the Advanced Research Project Agency network; we verify the validity and feasibility of our multi-attribute node importance evaluation method by removing the top six important nodes contrasted to the other methods. We believe that our work will have more practical implications for protecting the key nodes identified in the real world.
17 citations
TL;DR: In this article, the authors show how network theory may be applied to gain new and better insights into basic economic problems, starting with a precise definition of what is meant by acting and in particular by economic acting, and direct the line of argumentation toward solving the problem of how to aggregate economic decisions.
Abstract: The article attempts to show how network theory may be applied to gain new and better insights into basic economic problems. Starting with a precise definition of what is meant by acting and, in particular, by economic acting, we direct the line of argumentation toward solving the problem of how to aggregate economic decisions. Results indicate that network theory might well prove itself to be a powerful instrument in developing a theory of human behavior much more comprehensive than currently used models.
17 citations
TL;DR: This study provides a set of novel tools that can substantially enhance the extent to which network metrics can be employed to understand, and manage for, metapopulation persistence.
Abstract: Network analysis is gaining increasing importance in conservation planning. However, which network metrics are the best predictors of metapopulation persistence is still unresolved. Here, we identify a critical limitation of graph theory-derived network metrics that have been proposed for this purpose: their omission of node self-connections. We resolve this by presenting modifications of existing network metrics, and developing entirely new metrics, that account for node self-connections. Then, we illustrate the performance of these new and modified metrics with an age-structured metapopulation model for a real-world marine reserve network case study, and we evaluate the robustness of our findings by systematically varying particular features of that network. Our new and modified metrics predict metapopulation persistence much better than existing metrics do, even when self-connections are weak. Existing metrics become good predictors of persistence only when self-connections are entirely absent, an unrealistic scenario in the overwhelming majority of metapopulation applications. Our study provides a set of novel tools that can substantially enhance the extent to which network metrics can be employed to understand, and manage for, metapopulation persistence.
17 citations
TL;DR: In this article, the vortex interactions in two-dimensional decaying isotropic turbulence were studied and the vortical interaction network can be characterized by a weighted scale-free network.
Abstract: The present paper reports on our effort to characterize vortical interactions in complex fluid flows through the use of network analysis. In particular, we examine the vortex interactions in two-dimensional decaying isotropic turbulence and find that the vortical interaction network can be characterized by a weighted scale-free network. It is found that the turbulent flow network retains its scale-free behavior until the characteristic value of circulation reaches a critical value. Furthermore, we show that the two-dimensional turbulence network is resilient against random perturbations but can be greatly influenced when forcing is focused towards the vortical structures that are categorized as network hubs. These findings can serve as a network-analytic foundation to examine complex geophysical and thin-film flows and take advantage of the rapidly growing field of network theory, which complements ongoing turbulence research based on vortex dynamics, hydrodynamic stability, and statistics. While additional work is essential to extend the mathematical tools from network analysis to extract deeper physical insights of turbulence, an understanding of turbulence based on the interaction-based network-theoretic framework presents a promising alternative in turbulence modeling and control efforts.
17 citations