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

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).

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Year of publication:	2012
Authors:	Gueguim Kana, E.B. ; Oloke, J.K. ; Lateef, A. ; Adesiyan, M.O.
Published in:	Renewable Energy. - Elsevier, ISSN 0960-1481. - Vol. 46.2012, C, p. 276-281
Publisher:	Elsevier
Subject:	Biogas production \| Artificial intelligence \| Artificial Neural Network \| Bioprocess optimization \| Genetic Algorithm \| Mixed substrates

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010805348