Publication detail
Boscovich fuzzy regression line
ŠKRABÁNEK, P. MAREK, J. POZDÍLKOVÁ, A.
English title
Boscovich fuzzy regression line
Type
journal article in Web of Science
Language
en
Original abstract
We introduce a new fuzzy linear regression method. The method is capable of approximating fuzzy relationships between an independent and a dependent variable. The independent and dependent variables are expected to be a real value and triangular fuzzy numbers, respec-tively. We demonstrate on twenty datasets that the method is reliable, and it is less sensitive to outliers, compare with possibilistic-based fuzzy regression methods. Unlike other commonly used fuzzy regression methods, the presented method is simple for implementation and it has linear time-complexity. The method guarantees non-negativity of model parameter spreads.
English abstract
We introduce a new fuzzy linear regression method. The method is capable of approximating fuzzy relationships between an independent and a dependent variable. The independent and dependent variables are expected to be a real value and triangular fuzzy numbers, respec-tively. We demonstrate on twenty datasets that the method is reliable, and it is less sensitive to outliers, compare with possibilistic-based fuzzy regression methods. Unlike other commonly used fuzzy regression methods, the presented method is simple for implementation and it has linear time-complexity. The method guarantees non-negativity of model parameter spreads.
Keywords in English
fuzzy linear regression; non-symmetric triangular fuzzy number; least absolute value; Boscovich regression line; outlier
Released
23.03.2021
Publisher
MDPI
Location
Basel, Switzerland
ISSN
2227-7390
Volume
9
Number
6
Pages from–to
1–14
Pages count
14
BIBTEX
@article{BUT171143,
author="Pavel {Škrabánek} and Jaroslav {Marek} and Alena {Pozdílková},
title="Boscovich fuzzy regression line",
year="2021",
volume="9",
number="6",
month="March",
pages="1--14",
publisher="MDPI",
address="Basel, Switzerland",
issn="2227-7390"
}