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NISCAIR PUBLICATIONS >
Research Journals >
Indian Journal of Chemical Technology (IJCT) >
IJCT Vol.18 [2011] >
IJCT Vol.18(3) [May 2011] >
| Title: | Estimation of dynamic viscosities of vegetable oils using artificial neural networks |
| Authors: | Aksoy, Fatih
Yabanova, İsmail
Bayrakçeken, Hüseyin |
| Keywords: | Dynamic viscosity
Vegetable oils
Artificial neural networks |
| Issue Date: | May-2011 |
| Publisher: | NISCAIR-CSIR, India |
| Abstract: | In this study, viscosities of raw sunflower
and corn oils are measured at 1°C intervals between 0-100°C. Experimental
results are fitted to six equations that are used in viscosity estimation and
the correlation coefficients are determined. The best correlation coefficient is
obtained using In( )=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. |
| Page(s): | 227-233 |
| CC License: |  CC Attribution-Noncommercial-No Derivative Works 2.5 India |
| ISSN: | 0975-0991 (Online); 0971-457X (Print) |
| Source: | IJCT Vol.18(3) [May 2011]
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