Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/47276

TitleCombination of expert decision and learned based Bayesian Networks for multi-scale mechanical analysis of timber elements
Author(s)Sousa, Hélder S.
Prieto-Castrillo, Francisco
Matos, José C.
Branco, Jorge M.
Lourenço, Paulo B.
KeywordsBayesian Network
Timber
Multi-scale analysis
Expert systems
Learning algorithms
Ranking
Bayesian Networks
Issue date2018
PublisherElsevier
JournalExpert Systems with Applications
Abstract(s)The use of Bayesian Networks allows to organize and correlate information gathered from different sources and its optimization may incorporate restrictions adjusting the network based on expert knowledge and network operativeness, in such a way that it may satisfactorily represent a given domain. The main goal of this paper is to study if an optimized learned Bayesian Network may be used as a prior structure for an expert based network of an engineering structural material analysis. The methodology is applied to a database of results from an experimental campaign that focused on the mechanical characterization of timber elements recovered from an early 20th century building. To that study case it is evidenced that through a suitable combination of model averaging and supervision steps it is possible to achieve robust and reliable models to underpin the causal structure of a typical multi-scale timber analysis.
TypeArticle
Description"Available online 3 October 2017"
URIhttp://hdl.handle.net/1822/47276
DOI10.1016/j.eswa.2017.09.060
ISSN0957-4174
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:ISISE - Artigos em Revistas Internacionais

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