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Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

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  • Shuai Lin
  • Yanhui Wang
  • Limin Jia
  • Yang Li

Abstract

In view of the negative impact of component importance measures based on system reliability theory and centrality measures based on complex networks theory, there is an attempt to provide improved centrality measures (ICMs) construction method with fuzzy integral for measuring the importance of components in electromechanical systems in this paper. ICMs are the meaningful extension of centrality measures and component importance measures, which consider influences on function and topology between components to increase importance measures usefulness. Our work makes two important contributions. First, we propose a novel integration method of component importance measures to define ICMs based on Choquet integral. Second, a meaningful fuzzy integral is first brought into the construction comprehensive measure by fusion multi-ICMs and then identification of important components which could give consideration to the function of components and topological structure of the whole system. In addition, the construction method of ICMs and comprehensive measure by integration multi-CIMs based on fuzzy integral are illustrated with a holistic topological network of bogie system that consists of 35 components.

Suggested Citation

  • Shuai Lin & Yanhui Wang & Limin Jia & Yang Li, 2017. "Component Importance Measure Computation Method Based Fuzzy Integral with Its Application," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-18, August.
    • Handle: RePEc:hin:jnddns:7842596
    DOI: 10.1155/2017/7842596
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    Cited by:

    1. Xia, Weifu & Wang, Yanhui & Hao, Yucheng, 2023. "Modeling failure propagation to analyze the vulnerability of the complex electromechanical systems under network attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 613(C).

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