Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of blogas production
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...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/11978/1/PID88.pdf |
| Summary: | 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. |
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