Modeling Color Fading Ozonation of Dyed Textile Using Artificial Intelligence  
Author Zhenglei He


Co-Author(s) Kim-Phuc Tran; Sébastien Thomassey; Xianyi Zeng; Changhai Yi


Abstract Textile products with faded effect achieved via ozonation are increasingly popular recently. In this study, the effects of ozonation in terms of pH, temperature, water pickup, time and original colors on the color fading performance of reactive-dyed cotton are modeled using Extreme Learning Machine (ELM), Support Vector Regression (SVR) and Random Forest Regression (RFR) respectively. It is found that RF and SVR perform better than ELM in this issue, but SVR is more recommended to be used in the real application due to its balance predicting performance and less training time.


Keywords Artificial intelligence, Modeling, Color Fading, Ozonation, Textile
    Article #:  DSBFI19-45
Proceedings of ISSAT International Conference on Data Science in Business, Finance and Industry
July 3-5, 2019 - Da Nang, Vietnam