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  • 标题:Network growth models: A behavioural basis for attachment proportional to fitness
  • 本地全文:下载
  • 作者:Michael Bell ; Supun Perera ; Mahendrarajah Piraveenan
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2017
  • 卷号:7
  • 期号:1
  • DOI:10.1038/srep42431
  • 语种:English
  • 出版社:Springer Nature
  • 摘要:Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process. In particular, it is proven by analytical and numerical methods that in homogeneous networks, the minimisation of maximum exposure to node unfitness leads to attachment probabilities that are proportional to node fitness. This result is then extended to heterogeneous networks, with supply chain networks being used as an example.
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