As the need for quickly exploring a textile manufacturing process is increasingly costly along
with the complexity in the process. The development of manufacturing process modeling has …

Polymer based textile composites have gained much attention in recent years and gradually
transformed the growth of industries especially automobiles, construction, aerospace and …

This paper presents a new hybrid approach for the prediction of functional properties ie, self-
cleaning efficiency, antimicrobial efficiency and ultraviolet protection factor (UPF), of titanium …

Multi-ply yarns have been used as the main structure to form strands, braids, and fabrics.
Thus, various strategies including experimental, numerical, and analytical models have …

This paper represents the efficiency of machine learning tool, ie, artificial neural network
(ANN), for the prediction of functional properties of nano titanium dioxide coated cotton …

The acoustic emission (AE) technique is widely used at the present time for almost any kind
of material characterization. The main aim of the present study was to predict the tensile …

In this study, an artificial neural network (ANN) is used for the prediction of tensile strength of
nano titanium dioxide (TiO2) coated cotton. The coating process was performed by …

Yarn quality is an important factor that influences the subsequent products quality.
Employing artificial intelligence technologies can lead to more objective yarn testing …

The final attenuation and twisting of fiber take place at ring spinning machine and hence its
optimized performance is very crucial in terms of yarn quality. Drafting at ring spinning …

With the continuous development of deep learning, due to the complexity of the deep neural
network structure and the limitation of training time, some scholars have proposed broad …