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

TL;DR

This paper introduces a hybrid method combining data-driven techniques and expert input to construct fuzzy numbers, enhancing interpretability and consistency in fuzzy modeling.

Contribution

It extends the Deck of Cards framework with a convex fuzzy $k$-Means pipeline, enabling interactive, validated fuzzy number construction from data and expert knowledge.

Findings

Method ensures interpretability and adaptability.

Intermediate outputs facilitate expert validation.

Approach maintains consistency between data and expert semantics.

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 $k$-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.