Details

Autor(en) / Beteiligte

• Chen, Zhao
• Zhou, Chengzhi
• Zhou, Yijun
• Zhu, Lingyun
• Lu, Ting
• Liu, Guohua

Titel

Multi-dimensional Regression for Colour Prediction in Pad Dyeing

Ist Teil von

• Cloud Computing and Security, p.675-687

Ort / Verlag

Cham: Springer International Publishing

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• This paper aims to predict fabric colours by analyzing the relationship between multiple process parameters and colours of dyed fabrics in pad dyeing. The task is approached as a multi-dimensional regression problem. Within the framework of machine learning designed for colour prediction, two models, back-propagation neural network (BPNN) and multi-dimensional support vector regressor (M-SVR) are implemented. The process parameters are fed to these multi-dimensional regression models to predict the fabric colours measured in CIELAB values. The raw data used in our study are directly provided by a dyeing and printing manufacturer. As our experiments show, BPNN outperforms M-SVR with a relatively large data set while M-SVR is more accurate than BPNN is with a relatively small data set.