An artificial neural network approach to prediction of the colorimetric values of the stripped cotton fabrics

BALCI O., OGULATA S. N., ŞAHİN C., OĞULATA R. T.

FIBERS AND POLYMERS, cilt.9, sa.5, ss.604-614, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 9 Sayı: 5
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1007/s12221-008-0096-z
  • Dergi Adı: FIBERS AND POLYMERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.604-614
  • Anahtar Kelimeler: Stripping, L*, Delta E, Artificial neural network, Levenberg-Marquardt, ANOVA
  • Çukurova Üniversitesi Adresli: Evet

Özet

This paper presents an artificial neural network (ANN) modeling by Levenberg-Marquardt (LM) algorithm for predicting the colorimetric values of the stripped cotton fabrics dyed using commercial reactive dyes. Achieving the expected efficiency in the application of stripping process is a very important aspect for the success of the reproduction. In the study, the predictions of L* and Delta E colorimetric values of stripped cotton samples for different stripping applications by artificial neural network are reported. We set up different network structures with different number of nodes in the hidden layer, the number of inputs and MSE of results as stopping criteria in order to get the best fitting model. According to the result of the best neural network models predicting L* and Delta E, we achieved 97 % of R for both of them. We are able to predict the L* value of the stripped samples using some working parameters as inputs with only 1.2 % error. We think that our results are very promising and the predictions of L* and Delta E values of stripped samples before applying any process are possible using the ANN model set up in the study, especially for L*.