Abdul Sahli, Fakharudin and Md Nasir, Sulaiman and Jailani, Salihon and Norazwina, Zainol (2013) Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production. In: Proceedings of the 4th International Conference on Computing and Informatics (ICOCI 2013) , 28-30 August 2013 , Kuching, Sarawak. pp. 121-126. (088).
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Abstract
This paper proposed a framework to model and optimises a biogas production using artificial neural networks and genetic algorithms. The intelligence computation was applied to achieve a better model and optimisation compared to a mathematical modeling. Two training approaches were used to train a set of neural networks design. The trained networks model predictions were used to generate a maximum biogas output assisted by genetic algorithms optimisation. The result showed that modeling accuracy with low error will not give a better yield. It also reported a 0.44% increase of maximum biogas yield from the published result.
| Item Type: | Conference or Workshop Item (Lecture) |
|---|---|
| Uncontrolled Keywords: | Neural network; Genetic algorithms; Modeling; Optimisation |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Chemical & Natural Resources Engineering Faculty of Computer System And Software Engineering |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 22 Jan 2021 04:14 |
| Last Modified: | 22 Jan 2021 04:14 |
| URI: | http://umpir.ump.edu.my/id/eprint/28367 |
| Download Statistic: | View Download Statistics |
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