J. Kumar and A. Bansal
Biodiesel, transesterification, artificial neural network, flash point, fire point, viscosity, density
Soybean oil was transesterified with methanol in the presence of alkaline catalyst to produce methyl esters commonly known as biodiesel. Biodiesel–diesel blends were prepared and tested in laboratory for flash point, fire point, viscosity and density. Seven neural network architectures, three training algorithms along with ten different sets of weight and biases were examined to predict the above-mentioned properties of diesel and biodiesel blends. The best-suited neural network and training algorithm were selected and further generalized to improve its performance by using early stopping technique. The results showed that the neural network having an architecture 2-7-4 with Levenberg–Marquardt algorithm gave the best estimate for the properties of diesel–biodiesel blends.
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