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Application of response surface methodology and artificial neural network on pyrolysis of safflower seed press cake

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In this study, mathematical correlation between the process variables and product yields for pyrolysis of safflower seed press cake (SPC) in fixed-bed reactor was investigated by using the response surface methodology (RSM) and artificial neural networks (ANNs). The RSM results showed that the second-order response model can be used to describe the relationship between the various factors and the response. Several feed-forward fully connected neural networks were investigated and optimal configuration of the ANN model was obtained. The results revealed that the ANN model could be considered as an alternative to RSM and practical modeling technique for the pyrolysis product yields.
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Keywords: Fixed-bed reactor; neural network; product yields; pyrolysis; response surface methodology

Document Type: Research Article

Affiliations: 1: Department of Food Engineering, Sakarya University, Sakarya, Turkey 2: Department of Mechanical Engineering, Sakarya University, Sakarya, Turkey

Publication date: April 17, 2016

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