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

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Abstract

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 ΔE 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 ΔE, 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 ΔE values of stripped samples before applying any process are possible using the ANN model set up in the study, especially for L*.

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Authors and Affiliations

  1. Department of Textile Engineering, Fac. Engineering & Architecture, Cukurova University, Adana, 01330, Turkey

    Onur Balci & R. Tuğrul Oğulata

  2. Department of Industrial Engineering, Fac. Engineering & Architecture, Cukurova University, Adana, 01330, Turkey

    S. Noyan Oğulata & Cenk Şahin

Authors
  1. Onur Balci
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  2. S. Noyan Oğulata
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  3. Cenk Şahin
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  4. R. Tuğrul Oğulata
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Correspondence to Onur Balci.

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Balci, O., Noyan Oğulata, S., Şahin, C. et al. An artificial neural network approach to prediction of the colorimetric values of the stripped cotton fabrics. Fibers Polym 9, 604–614 (2008). https://doi.org/10.1007/s12221-008-0096-z

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  • DOI: https://doi.org/10.1007/s12221-008-0096-z

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