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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my.um.eprints.45192019-12-06T07:45:39Z http://eprints.um.edu.my/4519/ Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks Baroutian, S. Aroua, M.K. Abdul Raman, Abdul Aziz Sulaiman, N.M.N. TA Engineering (General). Civil engineering (General) 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. 2008 Article PeerReviewed Baroutian, S. and Aroua, M.K. and Abdul Raman, Abdul Aziz and Sulaiman, N.M.N. (2008) Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks. Journal of Applied Sciences, 8 (10). pp. 1938-1943. ISSN 18125654 (ISSN) |
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TA Engineering (General). Civil engineering (General) Baroutian, S. Aroua, M.K. Abdul Raman, Abdul Aziz Sulaiman, N.M.N. Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks |
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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. |
format |
Article |
author |
Baroutian, S. Aroua, M.K. Abdul Raman, Abdul Aziz Sulaiman, N.M.N. |
author_facet |
Baroutian, S. Aroua, M.K. Abdul Raman, Abdul Aziz Sulaiman, N.M.N. |
author_sort |
Baroutian, S. |
title |
Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks |
title_short |
Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks |
title_full |
Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks |
title_fullStr |
Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks |
title_full_unstemmed |
Prediction of palm oil-based methyl ester biodiesel density using artificial neural networks |
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prediction of palm oil-based methyl ester biodiesel density using artificial neural networks |
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2008 |
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http://eprints.um.edu.my/4519/ |
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1654960601252757504 |
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13.211869 |