Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization
Optimizing the process parameters of biodiesel production is the key to maximizing biodiesel yields. In this study, artificial neural network models integrated with ant colony optimization were developed to optimize the parameters of the two-step Cerbera manghas biodiesel production process: (1) est...
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| Format: | Article |
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MDPI
2019
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| author | Silitonga, Arridina Susan Mahlia, Teuku Meurah Indra Shamsuddin, Abd Halim Ong, Hwai Chyuan Milano, Jassinnee Kusumo, Fitranto Sebayang, Abdi Hanra Dharma, Surya Ibrahim, Husin Husin, Hazlina Mofijur, M. Rahman, S.M. Ashrafur |
| author_facet | Silitonga, Arridina Susan Mahlia, Teuku Meurah Indra Shamsuddin, Abd Halim Ong, Hwai Chyuan Milano, Jassinnee Kusumo, Fitranto Sebayang, Abdi Hanra Dharma, Surya Ibrahim, Husin Husin, Hazlina Mofijur, M. Rahman, S.M. Ashrafur |
| author_sort | Silitonga, Arridina Susan |
| collection | UM |
| description | Optimizing the process parameters of biodiesel production is the key to maximizing biodiesel yields. In this study, artificial neural network models integrated with ant colony optimization were developed to optimize the parameters of the two-step Cerbera manghas biodiesel production process: (1) esterification and (2) transesterification. The parameters of esterification and transesterification processes were optimized to minimize the acid value and maximize the C. manghas biodiesel yield, respectively. There was excellent agreement between the average experimental values and those predicted by the artificial neural network models, indicating their reliability. These models will be useful to predict the optimum process parameters, reducing the trial and error of conventional experimentation. The kinetic study was conducted to understand the mechanism of the transesterification process and, lastly, the model could measure the physicochemical properties of the C. manghas biodiesel. © 2019 by the authors. |
| first_indexed | 2024-03-06T05:59:51Z |
| format | Article |
| id | um.eprints-23432 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:59:51Z |
| publishDate | 2019 |
| publisher | MDPI |
| record_format | dspace |
| spelling | um.eprints-234322020-01-14T05:05:18Z http://eprints.um.edu.my/23432/ Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization Silitonga, Arridina Susan Mahlia, Teuku Meurah Indra Shamsuddin, Abd Halim Ong, Hwai Chyuan Milano, Jassinnee Kusumo, Fitranto Sebayang, Abdi Hanra Dharma, Surya Ibrahim, Husin Husin, Hazlina Mofijur, M. Rahman, S.M. Ashrafur TJ Mechanical engineering and machinery Optimizing the process parameters of biodiesel production is the key to maximizing biodiesel yields. In this study, artificial neural network models integrated with ant colony optimization were developed to optimize the parameters of the two-step Cerbera manghas biodiesel production process: (1) esterification and (2) transesterification. The parameters of esterification and transesterification processes were optimized to minimize the acid value and maximize the C. manghas biodiesel yield, respectively. There was excellent agreement between the average experimental values and those predicted by the artificial neural network models, indicating their reliability. These models will be useful to predict the optimum process parameters, reducing the trial and error of conventional experimentation. The kinetic study was conducted to understand the mechanism of the transesterification process and, lastly, the model could measure the physicochemical properties of the C. manghas biodiesel. © 2019 by the authors. MDPI 2019 Article PeerReviewed Silitonga, Arridina Susan and Mahlia, Teuku Meurah Indra and Shamsuddin, Abd Halim and Ong, Hwai Chyuan and Milano, Jassinnee and Kusumo, Fitranto and Sebayang, Abdi Hanra and Dharma, Surya and Ibrahim, Husin and Husin, Hazlina and Mofijur, M. and Rahman, S.M. Ashrafur (2019) Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization. Energies, 12 (20). p. 3811. ISSN 1996-1073, DOI https://doi.org/10.3390/en12203811 <https://doi.org/10.3390/en12203811>. https://doi.org/10.3390/en12203811 doi:10.3390/en12203811 |
| spellingShingle | TJ Mechanical engineering and machinery Silitonga, Arridina Susan Mahlia, Teuku Meurah Indra Shamsuddin, Abd Halim Ong, Hwai Chyuan Milano, Jassinnee Kusumo, Fitranto Sebayang, Abdi Hanra Dharma, Surya Ibrahim, Husin Husin, Hazlina Mofijur, M. Rahman, S.M. Ashrafur Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization |
| title | Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization |
| title_full | Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization |
| title_fullStr | Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization |
| title_full_unstemmed | Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization |
| title_short | Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization |
| title_sort | optimization of cerbera manghas biodiesel production using artificial neural networks integrated with ant colony optimization |
| topic | TJ Mechanical engineering and machinery |
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