Neural fuzzy model applied to autohydrolysis of Paulownia trihybrid
A central composite factorial design was used in conjunction with the software ANFIS Edit MATLAB 6.5 to develop fuzzy neural model that reproduced the experimental results of the dependent variables with errors less than 6%. The model is therefore effective with a view to simulating the autohydrolys...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2011 |
| País: | España |
| Institución: | Universidad de Huelva (UHU) |
| Repositorio: | Arias Montano. Repositorio Institucional de la Universidad de Huelva |
| Idioma: | inglés |
| OAI Identifier: | oai:ariasmontano.uhu.es:10272/10271 |
| Acceso en línea: | http://hdl.handle.net/10272/10271 |
| Access Level: | acceso abierto |
| Palabra clave: | Neural fuzzy modelling Paulownia Autohydrolysis Glucan Xilan Oligosaccharides |
| Sumario: | A central composite factorial design was used in conjunction with the software ANFIS Edit MATLAB 6.5 to develop fuzzy neural model that reproduced the experimental results of the dependent variables with errors less than 6%. The model is therefore effective with a view to simulating the autohydrolysis process. In this study it was evaluated the potential of a species trihybrid Paulownia fortunei, tormentosa and elongata as an industrial crop in terms of its contents in holocellulose, lignin, xylo-oligomers, monomers and other glucan and its use for making cellulose pulp. It was optimized biomass autohydrolysis processes to obtain valuable liquid and solid phases that can be used to produce liquid fuels and cellulosic pulp. The process was modelled in order to optimize the extraction of xylo-oligomers and xylose in the liquid phase while preserving the integrity of cellulose fibres. |
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