Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/12000
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.
Description: 227-233
URI: http://hdl.handle.net/123456789/12000
ISSN: 0975-0991 (Online); 0971-457X (Print)
Appears in Collections:IJCT Vol.18(3) [May 2011]

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