Publication detail

Boscovich fuzzy regression line

ŠKRABÁNEK, P. MAREK, J. POZDÍLKOVÁ, A.

Original Title

Boscovich fuzzy regression line

Type

journal article in Web of Science

Language

English

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.

Keywords

fuzzy linear regression; non-symmetric triangular fuzzy number; least absolute value; Boscovich regression line; outlier

Authors

ŠKRABÁNEK, P.; MAREK, J.; POZDÍLKOVÁ, A.

Released

23. 3. 2021

Publisher

MDPI

Location

Basel, Switzerland

ISBN

2227-7390

Periodical

Mathematics

Year of study

9

Number

6

State

Swiss Confederation

Pages from

1

Pages to

14

Pages count

14

URL

https://www.mdpi.com/2227-7390/9/6/685

Full text in the Digital Library

http://hdl.handle.net/11012/200895

BibTex

@article{BUT171143,
  author="Pavel {Škrabánek} and Jaroslav {Marek} and Alena {Pozdílková}",
  title="Boscovich fuzzy regression line",
  journal="Mathematics",
  year="2021",
  volume="9",
  number="6",
  pages="1--14",
  doi="10.3390/math9060685",
  issn="2227-7390",
  url="https://www.mdpi.com/2227-7390/9/6/685"
}