Publication detail

Boscovich fuzzy regression line

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

English title

Boscovich fuzzy regression line

Type

WoS Article

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.

Keywords in English

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

Released

2021-03-23

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",
  journal="Mathematics",
  year="2021",
  volume="9",
  number="6",
  pages="1--14",
  doi="10.3390/math9060685",
  url="https://www.mdpi.com/2227-7390/9/6/685"
}