Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2021, Cilt: 5 Sayı: 1, 41 - 49, 26.06.2021

Öz

Kaynakça

  • Abbasov T, Yuceer M, Yildiz Z, 2011. Prediction of Cleaning Efficiency of the Electromagnetic Filtration Based Fuzzy Inference System, International Review of Chemical Engineering Process using Adaptive Neural Network,I.RE.CH.E., 3(2):285-289.
  • Aboud A, 2013. Drying Characteristic of Apple Slices Undertaken the Effect of Passive Shelf Solar Dryer and Open Sun Drying. Pakistan Journal of Nutrition, 12(3):250-254.
  • Askari GR, Emam-Djomeh Z, Mousavi SM, 2008. Investigation of the Effects of Microwave Treatment on the Optical Properties of Apple Slices During Drying. Drying Technology 26:1362–1368.
  • Ceylan İ, Aktas M, Doğan H, 2006. Güneş Enerjili Kurutma Fırınında Elma Kurutması, Politechnics Journal, 289-294.
  • Choi IH, Pak JM, Ahn CK, Lee SH, Lim MT, Song MK, 2015. Arbitration Algorithm of Optical Flow Based on ANFIS for Visual Object Tracking. Measurement. 75:338–353.
  • Cui Z, Li C, Song C, Song Y, 2008. Combined Microwave-Vacuum and Freeze Drying of Carrot and Apple Chips. Drying Technology. 26:1517–1523.
  • Decareau RV, 1992. in: Encyclopedia of Food Science and Technology. John Wiley. New York., No:3, pp. 1772–1778.
  • Demirhan E, Ozbek B, 2011. Thin-Layer Drying Characteristics and Modeling of Celery Leaves Undergoing Microwave Treatment. Chemical Engineering Communications 198(7):957-975.
  • Esen H, Ozgen F, Esen M, Sengur A, 2009. Artificial neural network and wavelet neural network approaches for modeling of a solar air heater, Expert Systems with Applications, 36(8):11240-11248.
  • Jang JR, 1993. ANFIS: Adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man, 23: 665–685.
  • Kharb RK, Shimi SL, Chatterji S, Ansari MF, 2014. Modeling of solar PV module and maximum point tracking using ANFIS. Renew. Sustain. Energy Rev. 33:602–612.
  • Ochoa-Martínez LA, García-Quintero M, Morales-Castro J, Gallegos-Infante J, Martínez-Sánchez CE, Herman-Lara E, 2006. Effect of CaCl2 and convective Osmotic Drying on Texture And Preference of Apple. Journal of Food Quality, 29:583–595.
  • Öztürk H, 2008. Yenilenebilir Enerji Kaynakları ve Kullanımı. Teknik Yayınevi Mühendislik. Mimarlık Yayınları. Ankara.
  • Sharma R, Patterh MS, 2015. A New Pose Invariant Face Recognition System Using PCA Optik.126, 3483–3487.

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

Yıl 2021, Cilt: 5 Sayı: 1, 41 - 49, 26.06.2021

Öz

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.

Kaynakça

  • Abbasov T, Yuceer M, Yildiz Z, 2011. Prediction of Cleaning Efficiency of the Electromagnetic Filtration Based Fuzzy Inference System, International Review of Chemical Engineering Process using Adaptive Neural Network,I.RE.CH.E., 3(2):285-289.
  • Aboud A, 2013. Drying Characteristic of Apple Slices Undertaken the Effect of Passive Shelf Solar Dryer and Open Sun Drying. Pakistan Journal of Nutrition, 12(3):250-254.
  • Askari GR, Emam-Djomeh Z, Mousavi SM, 2008. Investigation of the Effects of Microwave Treatment on the Optical Properties of Apple Slices During Drying. Drying Technology 26:1362–1368.
  • Ceylan İ, Aktas M, Doğan H, 2006. Güneş Enerjili Kurutma Fırınında Elma Kurutması, Politechnics Journal, 289-294.
  • Choi IH, Pak JM, Ahn CK, Lee SH, Lim MT, Song MK, 2015. Arbitration Algorithm of Optical Flow Based on ANFIS for Visual Object Tracking. Measurement. 75:338–353.
  • Cui Z, Li C, Song C, Song Y, 2008. Combined Microwave-Vacuum and Freeze Drying of Carrot and Apple Chips. Drying Technology. 26:1517–1523.
  • Decareau RV, 1992. in: Encyclopedia of Food Science and Technology. John Wiley. New York., No:3, pp. 1772–1778.
  • Demirhan E, Ozbek B, 2011. Thin-Layer Drying Characteristics and Modeling of Celery Leaves Undergoing Microwave Treatment. Chemical Engineering Communications 198(7):957-975.
  • Esen H, Ozgen F, Esen M, Sengur A, 2009. Artificial neural network and wavelet neural network approaches for modeling of a solar air heater, Expert Systems with Applications, 36(8):11240-11248.
  • Jang JR, 1993. ANFIS: Adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man, 23: 665–685.
  • Kharb RK, Shimi SL, Chatterji S, Ansari MF, 2014. Modeling of solar PV module and maximum point tracking using ANFIS. Renew. Sustain. Energy Rev. 33:602–612.
  • Ochoa-Martínez LA, García-Quintero M, Morales-Castro J, Gallegos-Infante J, Martínez-Sánchez CE, Herman-Lara E, 2006. Effect of CaCl2 and convective Osmotic Drying on Texture And Preference of Apple. Journal of Food Quality, 29:583–595.
  • Öztürk H, 2008. Yenilenebilir Enerji Kaynakları ve Kullanımı. Teknik Yayınevi Mühendislik. Mimarlık Yayınları. Ankara.
  • Sharma R, Patterh MS, 2015. A New Pose Invariant Face Recognition System Using PCA Optik.126, 3483–3487.
Toplam 14 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Gıda Mühendisliği
Bölüm Article
Yazarlar

Zehra Yıldız 0000-0003-1304-4857

Leyla Gokayaz Bu kişi benim

Ercan Köse

Aydın Mühürcü

Yayımlanma Tarihi 26 Haziran 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 5 Sayı: 1

Kaynak Göster

APA Yıldız, Z., Gokayaz, L., Köse, E., Mühürcü, A. (2021). Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer. Eurasian Journal of Food Science and Technology, 5(1), 41-49.
AMA Yıldız Z, Gokayaz L, Köse E, Mühürcü A. Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer. EJFST. Haziran 2021;5(1):41-49.
Chicago Yıldız, Zehra, Leyla Gokayaz, Ercan Köse, ve Aydın Mühürcü. “Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer”. Eurasian Journal of Food Science and Technology 5, sy. 1 (Haziran 2021): 41-49.
EndNote Yıldız Z, Gokayaz L, Köse E, Mühürcü A (01 Haziran 2021) Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer. Eurasian Journal of Food Science and Technology 5 1 41–49.
IEEE Z. Yıldız, L. Gokayaz, E. Köse, ve A. Mühürcü, “Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer”, EJFST, c. 5, sy. 1, ss. 41–49, 2021.
ISNAD Yıldız, Zehra vd. “Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer”. Eurasian Journal of Food Science and Technology 5/1 (Haziran 2021), 41-49.
JAMA Yıldız Z, Gokayaz L, Köse E, Mühürcü A. Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer. EJFST. 2021;5:41–49.
MLA Yıldız, Zehra vd. “Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer”. Eurasian Journal of Food Science and Technology, c. 5, sy. 1, 2021, ss. 41-49.
Vancouver Yıldız Z, Gokayaz L, Köse E, Mühürcü A. Adaptive Neural Network Based Fuzzy Inference System for the Determination of Performance in the Solar Tray Dryer. EJFST. 2021;5(1):41-9.

Eurasian Journal of Food Science and Technology (EJFST)   e-ISSN: 2667-4890   Web: https://dergipark.org.tr/en/pub/ejfst   e-mail: foodsciencejournal@gmail.com