Using artificial neural network to predict colour properties of laser-treated 100% cotton fabric

O. N. Hung, L. J. Song, C. K. Chan, Chi Wai Kan, C. W M Yuen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)

Abstract

In this paper, artificial neural network (ANN) model was used for predicting colour properties of 100 % cotton fabrics, including colour yield (in terms of K/S value) and CIE L, a, and b values, under the influence of laser engraving process with various combination of laser processing parameters. Variables examined in the ANN model included fibre composition, fabric density (warp and weft direction), mass of fabric, fabric thickness and linear density of yarn (warp and weft direction). The ANN model was compared with a linear regression model where the ANN model produced superior results in prediction of colour properties of laser engraved 100 % cotton fabrics. The relative importance of the examined factors influencing colour properties was also investigated. The analysis revealed that laser processing parameters played an important role in affecting the colour properties of the treated 100 % cotton fabrics.
Original languageEnglish
Pages (from-to)1069-1076
Number of pages8
JournalFibers and Polymers
Volume12
Issue number8
DOIs
Publication statusPublished - 1 Dec 2011

Keywords

  • 100 % cotton fabric
  • Artificial neural network (ANN)
  • CIE L, a, and b values
  • Colour properties
  • K/S value
  • Laser engraving process

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Chemistry(all)
  • Polymers and Plastics

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