Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks
In this study, a new approach based on Artificial Neural Networks (ANNs) has been designed to estimate the density of pure palm oil-based methyl ester biodiesel. The experimental density data measured at various temperatures from 14 to 90°C at 1°C intervals were used to train the networks. The pre...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/4519/ |
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| Summary: | In this study, a new approach based on Artificial Neural Networks (ANNs) has been designed to estimate the density of pure palm oil-based methyl ester biodiesel. The experimental density data measured at various temperatures from 14 to 90°C at 1°C intervals were used to train the networks. The present research, applied a three layer back propagation neural network with seven neurons in the hidden layer. The results from the network are in good agreement with the measured data and the average absolute percent deviation is 0.29. The results of ANNs have also been compared with the results of empirical and theoretical estimations. © 2008 Asian Network for Scientific Information. |
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