Literature DB >> 18601470

Disorder and decision cost in spatial networks.

Massimiliano Zanin1, Javier M Buldú, P Cano, S Boccaletti.   

Abstract

We introduce the concept of decision cost of a spatial graph, which measures the disorder of a given network taking into account not only the connections between nodes but their position in a two-dimensional map. The influence of the network size is evaluated and we show that normalization of the decision cost allows us to compare the degree of disorder of networks of different sizes. Under this framework, we measure the disorder of the connections between airports of two different countries and obtain some conclusions about which of them is more disordered. The introduced concepts (decision cost and disorder of spatial networks) can easily be extended to Euclidean networks of higher dimensions, and also to networks whose nodes have a certain fitness property (i.e., one-dimensional).

Entities:  

Year:  2008        PMID: 18601470     DOI: 10.1063/1.2901916

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  3 in total

1.  Reduced synchronization persistence in neural networks derived from atm-deficient mice.

Authors:  Noah Levine-Small; Ziv Yekutieli; Jonathan Aljadeff; Stefano Boccaletti; Eshel Ben-Jacob; Ari Barzilai
Journal:  Front Neurosci       Date:  2011-04-04       Impact factor: 4.677

2.  Assortative mixing in spatially-extended networks.

Authors:  Vladimir V Makarov; Daniil V Kirsanov; Nikita S Frolov; Vladimir A Maksimenko; Xuelong Li; Zhen Wang; Alexander E Hramov; Stefano Boccaletti
Journal:  Sci Rep       Date:  2018-09-14       Impact factor: 4.379

3.  Multi-scale analysis of the European airspace using network community detection.

Authors:  Gérald Gurtner; Stefania Vitali; Marco Cipolla; Fabrizio Lillo; Rosario Nunzio Mantegna; Salvatore Miccichè; Simone Pozzi
Journal:  PLoS One       Date:  2014-05-08       Impact factor: 3.240

  3 in total

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