Hybrid Possibilistic-Probabilistic Approach to Uncertainty Quantification in Electromagnetic Compatibility Models

  • Nicola Toscani
  • Flavia GrassiEmail author
  • Giordano Spadacini
  • Sergio A. Pignari
Part of the PoliTO Springer Series book series (PTSS)


In this Chapter, possibility theory is briefly presented as a framework to deal with electromagnetic compatibility (EMC) problems characterized by incomplete or lack of knowledge (i.e., epistemic uncertainty) on the variability of some of the involved parameters. Accordingly, such parameters are modeled by fuzzy variables (characterized by possibility distributions), that, in real-case scenarios, usually coexist with random variables (characterized by probability distributions). This is the case of typical test setups for EMC verification, such as the radiated susceptibility case study here presented, where the uncertainty of output quantities strongly depends on some input parameters, whose probability distribution functions are unknown. To overcome this limitation, a hybrid approach is presented to propagate the uncertainty within the model, still retaining the possibilistic and probabilistic nature of the two sets of involved parameters. Two methods to aggregate the obtained random-fuzzy sets are presented and compared versus the results obtained by running fully-probabilistic Monte Carlo (MC) simulations, where all uncertain parameters were assigned known probability distributions.


Twisted-wire pair Epistemic uncertainty Possibility theory Hybrid probabilistic/possibilistic algorithm Random and fuzzy variables Radiated susceptibility 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Nicola Toscani
    • 1
  • Flavia Grassi
    • 1
    Email author
  • Giordano Spadacini
    • 1
  • Sergio A. Pignari
    • 1
  1. 1.Department of Electronics, Information and BioengineeringPolitecnico di MilanoMilanoItaly

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