Estimation of dynamic viscosities of vegetable oils using artificial neural networks

Aksoy F., YABANOVA İ., Bayrakceken H.

INDIAN JOURNAL OF CHEMICAL TECHNOLOGY, cilt.18, sa.3, ss.227-233, 2011 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 18 Sayı: 3
  • Basım Tarihi: 2011
  • Dergi Adı: INDIAN JOURNAL OF CHEMICAL TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.227-233
  • Manisa Celal Bayar Üniversitesi Adresli: Hayır

Özet

In this study, viscosities of raw sunflower and corn oils are measured at 1 degrees C intervals between 0-100 degrees C. Experimental results are fitted to six equations that are used in viscosity estimation and the correlation coefficients arc determined. The best correlation coefficient is obtained using In(mu)=a+b/(T+c) equation with 0.99972 and 0.99974 for sunflower and corn oil, respectively. In addition to this, viscosity values are obtained using artificial neural networks and the results are compared to the equation leading to the best correlation coefficient. Using artificial neural networks, the correlation coefficients are obtained as 0.999907 and 0.999925 for raw sunflower and corn oil respectively.