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Modeling and optimization of biogas production on saw dust and other co-substrates using Artificial Neural network and Genetic Algorithm

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  • Gueguim Kana, E.B.
  • Oloke, J.K.
  • Lateef, A.
  • Adesiyan, M.O.

Abstract

The joint challenge of global pollution and depletion of fossil fuels is driving intense search into alternative renewable sources. This paper reports the modeling and optimization of biogas production on mixed substrates of saw dust, cow dung, banana stem, rice bran and paper waste using Artificial Neural Network (ANN) coupling Genetic Algorithm (GA).

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:46:y:2012:i:c:p:276-281
    DOI: 10.1016/j.renene.2012.03.027
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    References listed on IDEAS

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    1. Li, Yebo & Park, Stephen Y. & Zhu, Jiying, 2011. "Solid-state anaerobic digestion for methane production from organic waste," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 821-826, January.
    2. Roy, Prokash C. & Datta, Amitava & Chakraborty, Niladri, 2010. "Assessment of cow dung as a supplementary fuel in a downdraft biomass gasifier," Renewable Energy, Elsevier, vol. 35(2), pages 379-386.
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