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Unsupervised spectral clustering for hierarchical modelling and criticality analysis of complex networks

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  • Fang, Yi-Ping
  • Zio, Enrico

Abstract

Infrastructure networks are essential to the socioeconomic development of any country. This article applies clustering analysis to extract the inherent structural properties of realistic-size infrastructure networks. Network components with high criticality are identified and a general hierarchical modelling framework is developed for representing the networked system into a scalable hierarchical structure of corresponding fictitious networks. This representation makes a multi-scale criticality analysis possible, beyond the widely used component-level criticality analysis, whose results obtained from zoom-in analysis can support confident decision making.

Suggested Citation

  • Fang, Yi-Ping & Zio, Enrico, 2013. "Unsupervised spectral clustering for hierarchical modelling and criticality analysis of complex networks," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 64-74.
    • Handle: RePEc:eee:reensy:v:116:y:2013:i:c:p:64-74
    DOI: 10.1016/j.ress.2013.02.021
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    References listed on IDEAS

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    1. Aaron Clauset & Cristopher Moore & M. E. J. Newman, 2008. "Hierarchical structure and the prediction of missing links in networks," Nature, Nature, vol. 453(7191), pages 98-101, May.
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    3. Zio, E. & Golea, L.R. & Rocco S., C.M., 2012. "Identifying groups of critical edges in a realistic electrical network by multi-objective genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 172-177.
    4. E. Zio, 2007. "From complexity science to reliability efficiency: a new way of looking at complex network systems and critical infrastructures," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 3(3/4), pages 488-508.
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    Cited by:

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    3. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    4. Xu, Zhaoyi & Saleh, Joseph Homer, 2021. "Machine learning for reliability engineering and safety applications: Review of current status and future opportunities," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
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    6. Wang, Shuliang & Lv, Wenzhuo & Zhang, Jianhua & Luan, Shengyang & Chen, Chen & Gu, Xifeng, 2021. "Method of power network critical nodes identification and robustness enhancement based on a cooperative framework," Reliability Engineering and System Safety, Elsevier, vol. 207(C).

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