Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CO2RBFN

Author
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-CO2RBFN, 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-CO2RBFN, other well-known data mining regression methods are used to model the transformation process.
Year of Publication
2017
Date Published
6
Conference Location
Cádiz (Spain)
ISBN Number
978-3-319-59152-0
DOI
10.1007/978-3-319-59153-7_63
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Number of Pages
733-744
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Notes

TIN2015-68454-R