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Dynamic risk assessment of complex systems using FCM

Author

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  • Afshin Jamshidi
  • Daoud Ait-kadi
  • Angel Ruiz
  • Mohamed Larbi Rebaiaia

Abstract

Analysing risk of today’s complex systems is challenging due to the complex and dynamic nature of systems. The current risk analysis tools are not able to take the complex interactions among risks into account and therefore they can’t predict the behaviour of risks accurately. In an attempt to overcome this shortcoming, this paper proposes an integrated generalised decision support tool using fuzzy cognitive maps for dynamic risk assessment of complex systems. The proposed approach has the ability to prioritise risk factors and more importantly predict and analysis the influences of each individual risk factor/risk set on the other risks or on the outcomes of complex and critical systems by taking into account probability of occurrence and consequences of risks and also considering the complex dependencies between risk factors. These features could provide practitioners with realistic results in critical industries and able them to manage risks more efficiently.

Suggested Citation

  • Afshin Jamshidi & Daoud Ait-kadi & Angel Ruiz & Mohamed Larbi Rebaiaia, 2018. "Dynamic risk assessment of complex systems using FCM," International Journal of Production Research, Taylor & Francis Journals, vol. 56(3), pages 1070-1088, February.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:3:p:1070-1088
    DOI: 10.1080/00207543.2017.1370148
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    Cited by:

    1. Shang, Du & Shang, Pengjian, 2022. "The dependence measurements based on martingale difference correlation and distance correlation: Efficient tools to distinguish different complex systems," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    2. Sahar AlMashaqbeh & Jose Eduardo Munive-Hernandez, 2023. "Risk Analysis under a Circular Economy Context Using a Systems Thinking Approach," Sustainability, MDPI, vol. 15(5), pages 1-17, February.

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