Neural network design and feature selection using principal component analysis and Taguchi method for identifying wood veneer defects

Production and Manufacturing Research

Volumn 2, Issue 1, 2014, Pages 291-308

  Yuce, Baris ^a   Mastrocinque, Ernesto ^b   Packianather, Michael Sylvester ^a   Pham, Duc ^c   Lambiase, Alfredo ^b   Fruggiero, Fabio ^d  

^a CARDIFF UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF SALERNO   (Italy)

^c UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^d UNIVERSITY OF BASILICATA   (Italy)

Author keywords

ANN; feature extraction; PCA; Taguchi analysis

Indexed keywords

DEFECTS; FEATURE EXTRACTION; NEURAL NETWORKS; QUALITY ASSURANCE; QUALITY CONTROL; TAGUCHI METHODS; VENEERS;

ANN CLASSIFIERS; CONTINUOUS IMPROVEMENTS; CRITICAL VARIABLES; ECONOMIC RECESSION; MANUFACTURING FIRMS; NEURAL NETWORK DESIGNS; PRODUCTION CYCLE; TAGUCHI ANALYSIS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84977091046     PISSN: None     EISSN: 21693277     Source Type: Journal    
DOI: 10.1080/21693277.2014.892442     Document Type: Article

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