Efficient Methane Production from Anaerobic Digestion of Cow Dung: An Optimization Approach
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- Gueguim Kana, E.B. & Oloke, J.K. & Lateef, A. & Adesiyan, M.O., 2012. "Modeling and optimization of biogas production on saw dust and other co-substrates using Artificial Neural network and Genetic Algorithm," Renewable Energy, Elsevier, vol. 46(C), pages 276-281.
- Matheri, A.N. & Ndiweni, S.N. & Belaid, M. & Muzenda, E. & Hubert, R., 2017. "Optimising biogas production from anaerobic co-digestion of chicken manure and organic fraction of municipal solid waste," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 756-764.
- Zareei, Samira & Khodaei, Jalal, 2017. "Modeling and optimization of biogas production from cow manure and maize straw using an adaptive neuro-fuzzy inference system," Renewable Energy, Elsevier, vol. 114(PB), pages 423-427.
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Keywords
methane production; mathematical model; biogas digester; optimization; determination coefficient;All these keywords.
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