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Minimisation of uncertainty in decision-making processes using optimised probabilistic Fuzzy Cognitive Maps: A case study for a rural sector

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  • Sacchelli, S.
  • Fabbrizzi, S.

Abstract

Several studies have focused on methods of increasing system and uncertainty knowledge for socio-economic and environmental policies; however, the nonlinearity and dynamism of real world increase the gap between uncertainty depiction and its evaluation in policy strategies. This work attempts to implement a methodology that is able to minimise uncertainty in decision support tools related to rural planning and management. Fuzzy Cognitive Maps, the Dempster–Shafer theory and nonlinear optimisation were applied to achieve the above-mentioned goal. The method was tested to describe suitable policies and intervention strategies to address the effects of the recent economic crisis in the agricultural sector.

Suggested Citation

  • Sacchelli, S. & Fabbrizzi, S., 2015. "Minimisation of uncertainty in decision-making processes using optimised probabilistic Fuzzy Cognitive Maps: A case study for a rural sector," Socio-Economic Planning Sciences, Elsevier, vol. 52(C), pages 31-40.
    • Handle: RePEc:eee:soceps:v:52:y:2015:i:c:p:31-40
    DOI: 10.1016/j.seps.2015.10.002
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    References listed on IDEAS

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    2. Zarrin, Mansour, 2022. "Inferring causal networks of health care resilience and safety performance indicators: A two-stage fuzzy cognitive map approach," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

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