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Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production

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
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