FUZZY REGRESSION MODEL BASED ON LR-TYPE NUMBERS WITH FUZZY SPREADS

This paper is focused on using LR-type fuzzy numbers with fuzzy spreads (one simplified subclass of Type-2 FSs) as coefficients of a fully fuzzy regression model with a single input. Input and output variables are represented as usual LR-type numbers (subclass of Type-1 FSs). The Ordinary Least Squares (OLS) may be used for model parameters estimation.

Authors

A. N. Konyukhov (ORCID: https://orcid.org/0000-0002-1523-7110)
K. V. Bukhensky
Arthur B. DuBois (ORCID: https://orcid.org/0009-0003-7374-7922)

Publication Details

Published: 2025-06-15
DOI: https://doi.org/10.21667/978-5-7722-0427-6-6-10
Primary Topic: Fuzzy Systems and Optimization
Type: article
Field-Weighted Citation Impact: 0.00

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article

FUZZY REGRESSION MODEL BASED ON LR-TYPE NUMBERS WITH FUZZY SPREADS

A. N. Konyukhov, K. V. Bukhensky, Arthur B. DuBois

Jun 15, 2025

Fuzzy Systems and Optimization

article

FUZZY REGRESSION MODEL BASED ON LR-TYPE NUMBERS WITH FUZZY SPREADS

A. N. Konyukhov, K. V. Bukhensky, Arthur B. DuBois

June 15, 2025article en

Abstract

Openalex Percentile: Top 78%

Fuzzy Systems and Optimization

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FUZZY REGRESSION MODEL BASED ON LR-TYPE NUMBERS WITH FUZZY SPREADS — A. N. Konyukhov, K. V. Bukhensky, et al. · (2025) | TGRS Research Map | TGRS