Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer

Zehra YILDIZ; Leyla GOKAYAZ; Ercan KÖSE; Aydın MÜHÜRCÜ

Makale detayları

Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer

Yazarlar:

Zehra YILDIZ | Leyla GOKAYAZ | Ercan KÖSE | Aydın MÜHÜRCÜ

Yayıncı:

İlknur BAĞDATLI

Ana Başlıklar:

Gıda teknolojisi

Dergi:

Eurasian Journal of Food Science and Technology 2021 Vol.5 Issue 1, pp.41-49

Belge Tipi:

Makale

Yayın Tarihi:

6/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000422303

eISSN:

2667-4890

Özet:

 

This study aims to apply the adaptive neural network based fuzzy inference system (ANFIS) were used to modeling the apple solar drying conditions in the solar tray dryer. Apple slices were dried by solar drying techniques as a solar tray dryer, exposure to direct sunlight and in the shade. Drying air temperature, the air humidity, apple slice load, apple slice thickness and solar drying time has been investigated with the prediction of the drying in the solar tray dryer on water loss, drying rate and shrinkage ratio. The model results clearly showed that the use of ANFIS led to more accurate results. The correlation coefficient (R2) values of the water loss, drying rate and shrinkage ratio were found as 0.9968, 0,9675 and 0,9918, the water loss, drying rate and shrinkage ratio respectively.

Makale detayları

Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer

Yazarlar: Zehra YILDIZ | Leyla GOKAYAZ | Ercan KÖSE | Aydın MÜHÜRCÜ

Yayıncı: İlknur BAĞDATLI

Ana Başlıklar: Gıda teknolojisi

Dergi: Eurasian Journal of Food Science and Technology 2021 Vol.5 Issue 1, pp.41-49

Belge Tipi: Makale

Yayın Tarihi: 6/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000422303

eISSN: 2667-4890

Sayı

Yazarlar:

Zehra YILDIZ | Leyla GOKAYAZ | Ercan KÖSE | Aydın MÜHÜRCÜ

Yayıncı:

İlknur BAĞDATLI

Ana Başlıklar:

Gıda teknolojisi

Dergi:

Eurasian Journal of Food Science and Technology 2021 Vol.5 Issue 1, pp.41-49

Belge Tipi:

Makale

Yayın Tarihi:

6/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000422303

eISSN:

2667-4890