Fabric handle prediction using neural networks

Handle is an important property of fabrics. In this work we tried to predict the handles of some worsted fabrics by their physical properties using a backpropagation network. Also an unsupervised kohonen network was used for clustering the fabrics. Physical properties of fabrics were measured by universal test equipments and hand values of the fabrics were determined by a panel of judges consisted of some textile experts. The results showed that the backpropagation network could predict the hand values of the untrained fabrics with average one degree of difference. Also the kohonen network could cluster the fabrics well and near to clustering of experts. These results show that these two kinds of neural networks are good tools for predicting hand values and clustering fabrics.