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2017 | OriginalPaper | Buchkapitel

Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CO\(^2\)RBFN

verfasst von : Francisco Charte Ojeda, Inmaculada Romero Pulido, Antonio Jesús Rivera Rivas, Eulogio Castro Galiano

Erschienen in: Advances in Computational Intelligence

Verlag: Springer International Publishing

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Abstract

Research in renewable energies is a global trend. One remarkable area is the biomass transformation into biotehanol, a fuel that can replace fossil fuels. A key step in this process is the pretreatment stage, where several variables are involved. The experimentation for determining the optimal values of these variables is expensive, therefore it is necessary to model this process. This paper focus on modeling the production of biotehanol from olive tree biomass by data mining methods. Notably, the authors present Reg-CO\(^2\)RBFN, an adaptation of a cooperative-competitive designing method for radial basis function networks. One of the main drawbacks in this modeling is the low number of instances in the data sets. To compare the results obtained by Reg-CO\(^2\)RBFN, other well-known data mining regression methods are used to model the transformation process.

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Metadaten
Titel
Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CORBFN
verfasst von
Francisco Charte Ojeda
Inmaculada Romero Pulido
Antonio Jesús Rivera Rivas
Eulogio Castro Galiano
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-59153-7_63