ArticleScientific reports2017
Network growth models: A behavioural basis for attachment proportional to fitness.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
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- Complex Network Analysis of Mass Violation, Specifically Mass Killing.Entropy (Basel, Switzerland) · 2022Article
- Game Theory in Defence Applications: A Review.Sensors (Basel, Switzerland) · 2022Review
- A generative network model of neurodevelopmental diversity in structural brain organization.Nature communications · 2021Observational
- Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic.Royal Society open science · 2021Article
- Prediction and prevention of disproportionally dominant agents in complex networks.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Investigating the Influence of Inverse Preferential Attachment on Network Development.Entropy (Basel, Switzerland) · 2020Article
- Detecting differences in the topology of scale-free networks grown under time-dynamic topological fitness.Scientific reports · 2020Article
- Network effects govern the evolution of maritime trade.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Raising the Connectome: The Emergence of Neuronal Activity and Behavior inFrontiers in cellular neuroscience · 2020Article
- Testing "efficient supply chain propositions" using topological characterization of the global supply chain network.PloS one · 2020Article
- Morphogenesis of Urban Water Distribution Networks: A Spatiotemporal Planning Approach for Cost-Efficient and Reliable Supply.Entropy (Basel, Switzerland) · 2018Article
- Network science approach to modelling the topology and robustness of supply chain networks: a review and perspective.Applied network science · 2017Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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