Title :
Pattern recognition for holonic manufacturing systems
Author :
Ferariu, L. ; Panescu, D.
Author_Institution :
Dept. of Autom. Control & Appl. Inf., “Gh. Asachi” Tech. Univ. of Iasi, Iasi, Romania
Abstract :
The paper addresses to the pattern recognition problem within the framework of holonic manufacturing systems. A novel methodology with enhanced adaptation capabilities devoted to features extraction is suggested. It involves a flexible genetic selection of relevant features, in accordance with the specific properties of the patterns that have to be recognized. The competing features are determined by means of principal component analysis, bi-dimensional Fourier transformation and grey-levels analysis. The problem is formulated as a multi-objective optimisation, addressing to both classification accuracy and parsimony. The experimental results reveal the improvement of overall performances of the pattern recognition subsystem.
Keywords :
Fourier transforms; feature extraction; grey systems; manufacturing systems; optimisation; pattern recognition; principal component analysis; bidimensional Fourier transformation; classification accuracy; features extraction; flexible genetic selection; grey-levels analysis; holonic manufacturing system; multiobjective optimisation; parsimony; pattern recognition problem; principal component analysis; Feature extraction; Genetics; Histograms; Optimization; Pattern recognition; Principal component analysis; Sociology;
Conference_Titel :
Control Conference (ECC), 2009 European
Conference_Location :
Budapest
Print_ISBN :
978-3-9524173-9-3
