A comparative study of fuzzy linear regression and multiple linear regression inagricultural studies: a case study of lentil yield management

Authors

KARIM SORKHEH
AHMAD KAZEMIFARD
SHAKIBA RAJABPOOR

DOI

10.3906/tar-1709-57

Abstract

This study investigates the advantages of two fuzzy linear regression (FLR) models, namely the Tanaka and the Savic and Pedrycz models, over multiple linear regression (MLR) for lentil yield management. We used a fuzzy approach to model the yield of lentil genotypes in which the input is crisp and the output fuzzy. Moreover, after finding FLR equations, we estimated the output corresponding to the collection of fuzzy inputs by using fuzzy algebraic operations and an appropriate defuzzification method known as the center of area method. Results showed the superiority of the Tanaka model over MLR because of reducing the included variables, especially variables available after harvest. The study also emphasizes the advantage of the Savic and Pedrycz model in comparison to the other two models with a smaller error rate.

Keywords

Fuzzy linear regression, multiple linear regression, Lens culinaris

First Page

402

Last Page

411

Recommended Citation

SORKHEH, KARIM; KAZEMIFARD, AHMAD; and RAJABPOOR, SHAKIBA (2018) "A comparative study of fuzzy linear regression and multiple linear regression inagricultural studies: a case study of lentil yield management," Turkish Journal of Agriculture and Forestry: Vol. 42: No. 6, Article 3. https://doi.org/10.3906/tar-1709-57
Available at: https://journals.tubitak.gov.tr/agriculture/vol42/iss6/3