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Peer-reviewedCC BY 4.0Fuzzy Sets and Systems

A hybrid approach for building fuzzy numbers based on data and expert knowledge

  • Diego García-Zamora
  • José Rui Figueira
  • Miguel Couceiro
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Abstract

This paper presents a hybrid socio-technical methodology for constructing fuzzy numbers from numerical data while incorporating expert knowledge through an interactive Deck of Cards (DoC) process. The approach extends the existing DoC membership function construction framework by introducing a data-driven pipeline based on a convex version of Fuzzy C-Means, in which each computational step produces intermediate outputs that are translated into card-based structures for expert validation and tuning. The proposed method ensures interpretability, adaptability, and consistency between empirical evidence and expert semantics.

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Cite

BibTeXRIS
BibTeX
@article{garciazamora2026hybrid,
  title = {{A hybrid approach for building fuzzy numbers based on data and expert knowledge}},
  author = {Diego García-Zamora and José Rui Figueira and Miguel Couceiro},
  journal = {Fuzzy Sets and Systems},
  year = {2026},
  month = oct,
  doi = {10.1016/j.fss.2026.110000},
  url = {https://hal.science/hal-05830343v1},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - A hybrid approach for building fuzzy numbers based on data and expert knowledge
AU  - Diego García-Zamora
AU  - José Rui Figueira
AU  - Miguel Couceiro
PY  - 2026
DA  - 2026/10/22
JO  - Fuzzy Sets and Systems
DO  - 10.1016/j.fss.2026.110000
UR  - https://hal.science/hal-05830343v1
AB  - This paper presents a hybrid socio-technical methodology for constructing fuzzy numbers from numerical data while incorporating expert knowledge through an interactive Deck of Cards (DoC) process. The approach extends the existing DoC membership function construction framework by introducing a data-driven pipeline based on a convex version of Fuzzy C-Means, in which each computational step produces intermediate outputs that are translated into card-based structures for expert validation and tuning. The proposed method ensures interpretability, adaptability, and consistency between empirical evidence and expert semantics.
SN  - 0165-0114
ER  -