Applying artificial neural network technique and theory to study the hairiness of polyester/cotton blended yarn in warping process

The polyester/cotton blended yarn hairiness in warping process is affected by fiber performance and processing parameters, which makes its prediction difficult. Among these processes, warping process parameters play an important role in warping yarn hairiness through warping process. To examine the effect of various warping process parameters on yarn hairiness, in this work, we used the ANN method to predict the hairiness of polyester/cotton yarn in warping process with warping process parameters. The results show that the hairiness can be well predicted by us. The results show that the ANN model yields more accurate and stable predictions, which indicates that the ANN theory is an effective and viable modeling method.