The purpose of this study is to predict and optimize the fish biodiesel characteristics using its permittivity properties. The parameters of biodiesel permittivity properties (έ, dielectric constant and ε″, loss factor) at microwave frequencies of (434, 915 and 2450 MHz) were used as input variables. The fish biodiesel characteristics as fatty acid methyl ester (FAME) content and flash point (FP) at three different level of reaction time (3, 9 and 27 min) and catalyst concentration (1, 1.5 and 2 % w/woil) were selected as output parameters for the models. Linear regression (LR), the multi-layer perceptron (MLP) and the radial basis function (RBF) as the methods of artificial neural networks (ANN), and the response surface method were compared for prediction and optimization of FAME content and flash point. A comparison of the results showed that RBF recorded higher coefficient of determination at frequency of 2450 MHz as 0.999 and 0.988 and lower root mean square error as 0.009 and 0.023 for FAME content and flash point, respectively. The optimum condition was obtained using RSM by FAME content of 89.88% and flash point of 152.7 °C with desirability of 0.998.
کلید واژگان :Permittivity properties, Prediction, FAME content, Optimization, RSM
ارزش ریالی : 600000 ریال
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