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dc.contributor.authorCórdova-Suárez, M.-
dc.contributor.authorSosa-Cárdenas, J.-
dc.contributor.authorCifuentes-Suárez, Y.-
dc.contributor.authorSánchez-Almeida, L.-
dc.date.accessioned2022-06-28T17:49:01Z-
dc.date.available2022-06-28T17:49:01Z-
dc.date.issued2020-
dc.identifier.urihttps://www.e3s-conferences.org/articles/e3sconf/abs/2020/27/e3sconf_icesd2020_05006/e3sconf_icesd2020_05006.html-
dc.identifier.urihttp://repositorio.uti.edu.ec//handle/123456789/3343-
dc.description.abstractThe energy potential of biogas is estimated from the biomass quantity, that is, a biodegradability values obtained from the organic fraction of municipal solid waste (MSW). In this study, the percentage contribution of each and every type of waste was quantified according to the waste classification., In addition, the waste generation data was projected by applying both artificial neural network (ANN) and mathematical models and 4 types of biomass wastes which accounts for a contribution of about 63% of the total waste sampled were obtained. The projection of the weights of the waste was carried out from 2015 to 2030, with the application of the neural network model with Back-propagation. All in all, under the application of the mathematical models, it has been shown that the Ecuadorian model predicted not only a high average volume, but also a large annual value of biogas energy. © The Authors, published by EDP Sciences, 2020.es
dc.language.isoenges
dc.publisherE3S Web of Conferences. Volume 167. 1th International Conference on Environmental Science and Development, ICESD 2020. Barcelona. 10 February 2020 through 12 February 2020es
dc.rightsopenAccesses
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es
dc.titleLong-Term evaluation of biogas energy potential based on the neuronal network approaches
dc.typearticlees
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