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Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization

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Department of Mechanical Engineering, Politeknik Negeri Medan, Medan 20155, Indonesia
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School of Information, Systems and Modelling, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia
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Institute of Sustainable Energy, Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia
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Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
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Department of Computer Science & Information Technology, College of Computer Science & Information Technology Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia
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Department of Petroleum Engineering, Faculty of Engineering, Universiti Teknologi Petronas, Persiaran UTP, Seri Iskandar 32610, Perak, Malaysia
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Biofuel Engine Research Facility (BERF), Queensland University of Technology, Brisbane, QLD 4000, Australia
*
Authors to whom correspondence should be addressed.
Energies 2019, 12(20), 3811; https://doi.org/10.3390/en12203811
Received: 26 July 2019 / Revised: 24 August 2019 / Accepted: 4 September 2019 / Published: 9 October 2019
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. View Full-Text
Keywords: Cerbera manghas oil; biodiesel; artificial neural networks; ant colony optimization; kinetic study Cerbera manghas oil; biodiesel; artificial neural networks; ant colony optimization; kinetic study
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Silitonga, A.S.; Mahlia, T.M.I.; Shamsuddin, A.H.; Ong, H.C.; Milano, J.; Kusumo, F.; Sebayang, A.H.; Dharma, S.; Ibrahim, H.; Husin, H.; Mofijur, M.; Rahman, S.M.A. Optimization of Cerbera manghas Biodiesel Production Using Artificial Neural Networks Integrated with Ant Colony Optimization. Energies 2019, 12, 3811.

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