An Application of Fuzzy Pearson Correlation Methods in Animal Sciences
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
How to evaluate an appropriate correlation to find the fuzzy relationship between variables is an important topic in the lactation milk yield and reproduction characteristics measurement. Especially when the data illustrate uncertain,\rinconsistent and incomplete type, fuzzy statistical technique has some theoric\rfeatures that help resolving unclear thinking in human logic and the source of\runcertainties in the natural structure of the data. Traditionally, we use Pearson’s Correlation Coefficient to measure the correlation between data with real\rvalue. However, when the data are composed of fuzzy numbers, it is not feasible to use such a traditional approach to determine the fuzzy correlation coefficient. This study proposes the calculation of fuzzy correlation with triangular\rof fuzzy data. Using Matlab application, fuzzy Pearson correlation coefficients\rand their membership degrees which belong to Holstein Friesian cows for the\rrelationship between lactation milk yield, the age of the animal at lactation,\rnumber of days milked, service period and first calving age were calculated (-\r0.0056; 0.95), (0.1419; 0.98), (-0.272;1.0) and (-0.2543; 0.90) respectively.\rThe membership degrees of the calculated fuzzy Pearson coefficient values are\rmore reliable and a consistent coefficient since it determines the size of the\rrelationship between the sets, which belong to variables.\rAs a result of the study, the fuzzy Pearson correlation coefficient analysis may\rbe preferred to calculate the degree of uncertainty and membership degrees\rbetween variables that should be used in studies to increase lactation milk\ryield.
Açıklama
Anahtar Kelimeler
Veterinerlik
Kaynak
Selcuk Journal of Agriculture and Food Sciences
WoS Q Değeri
Scopus Q Değeri
Cilt
35
Sayı
3
