eprintid: 2336
rev_number: 14
eprint_status: archive
userid: 1903
dir: disk0/00/00/23/36
datestamp: 2010-02-22 12:42:15
lastmod: 2016-04-20 12:04:19
status_changed: 2010-02-22 12:42:15
type: article
metadata_visibility: show
item_issues_count: 0
creators_name: Garcia Fernandez, Francisco
creators_name: García Esteban, Luis
creators_name: Palacios de Palacios, Paloma de
creators_name: Navarro Cano, Nieves
creators_name: Conde García, Marta
title: Prediction of standard particleboard mechanical properties utilizing an artificial neural network and subsequent comparison with a multivariate regression model
ispublished: pub
subjects: materiales
abstract: The physical properties (specific gravity, moisture content, thickness swelling and water absorption) and mechanical properties (internal bond strength, bending strength and modulus of elasticity) were determined on 93 Spanish-manufactured standard particleboards of different thicknesses selected randomly at the end of the production process. The testing methods of the corresponding European standards (EN) were used, except in the case of the thickness swelling and absorption tests, for which the Spanish UNE standard was used. The thickness and the values obtained for the physical properties were entered into an artificial neural network in order to predict the mechanical properties of the board. The fit was compared with the usual multivariate regression models. The use of a neural network made it possible to obtain the values of bending strength, modulus of elasticity and internal bond strength of the boards utilizing the known data, not only of thickness, moisture content and specific gravity, but also of thickness swelling and water absorption. The neural network proposed is much better adapted to the observed values than any of the multivariate regression models obtained.
date: 2008-08
date_type: published
publisher: INIA
official_url: http://www.inia.es/inia/contenidos/publicaciones/index.jsp?intranet=1&idcategoria=1359
full_text_status: public
publication: Investigación Agraria: Sistemas y Recursos Forestales
volume: 17
number: 2
pagerange: 178-187
institution: Montes
department: Ingenieria_Forestal
refereed: TRUE
issn: 1131-7965
rights: by-nc-nd
citation:   Garcia Fernandez, Francisco and García Esteban, Luis and Palacios de Palacios, Paloma de and Navarro Cano, Nieves and Conde García, Marta  (2008).  Prediction of standard particleboard mechanical properties utilizing an artificial neural network and subsequent comparison with a multivariate regression model.   "Investigación Agraria: Sistemas y Recursos Forestales", v. 17  (n. 2);   pp. 178-187.  ISSN 1131-7965.    
document_url: https://oa.upm.es/2336/1/INVE_MEM_2008_55033.pdf