10.57647/mathsci.2026.2003.17

Hybrid Fuzzy Regression: Performance Comparison of Symmetric and Asymmetric Triangular Fuzzy Data

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  • Reza Hozni1,
  • Behrouz Fathi Vajargah*2,
  • Mohamad Hassan Behzadi1,
  • Mojtaba Moradi3,
  1. Department of Statistics, SR. C., Islamic Azad University, Tehran, Iran
  2. Department of Statistics, University of Guilan, Rasht, Iran
  3. Department of Industrial Engineering, Faculty of East of Guilan, University of Guilan,Vajargah, Iran

Received: 2025-11-10

Revised: 2026-01-31

Accepted: 2026-02-10

Published in Issue 2026-09-30

Copyright (c) 2026 Reza Hozni, Behrouz Fathi Vajargah, Mohamad Hassan Behzadi, Mojtaba Moradi (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Hozni, R., Fathi Vajargah, B., Behzadi, M. H., & Moradi, M. (2026). Hybrid Fuzzy Regression: Performance Comparison of Symmetric and Asymmetric Triangular Fuzzy Data. Mathematical Sciences, 20(3). https://doi.org/10.57647/mathsci.2026.2003.17
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Abstract

This paper presents a comprehensive comparison between symmetrical and asymmetrical triangular fuzzy data within hybrid bivariate regression models, evaluating their performance through reliability measures and uncertainty quantification. Our study demonstrates that hybrid least squares fuzzy regression not only gener-alizes classical regression but also provides superior reliability metrics, with classical measures emerging as a special case of hybrid measures emerging as a special case of hybrid reliability under precise conditions.

Keywords

  • Fuzzy regression,
  • Hybrid reliability,
  • Triangular fuzzy numbers,
  • Weighted arithmetic,
  • Uncertainty quantification
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