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

• Main Authors: Fakharudin, Abdul Sahli, Sulaiman, Md Nasir, Salihon, Jailani, Zainol, Norazwina
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: QA76 Computer software
• Online Access: http://repo.uum.edu.my/11978/1/PID88.pdf; http://repo.uum.edu.my/11978/; http://www.icoci.cms.net.my/proceedings/2013/TOC.html
• Institution: Universiti Utara Malaysia

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.