Using artificial neural networks with graphical user interface to predict the strength of carded cotton yarns

Artificial neural networks (ANNs) are used in prediction fields. Yarn strength is one of the most important properties, because it reflects the quality of the yarn. The prediction process of yarn strength is very important from the technology side because many of generated forces in the spun yarns could be given by yarn strength. Data were collected from the United Commercial Industrial Company, Damascus, Syria. Then, artificial neural network algorithm was architected. Several neural networks were architected one of these has been chosen, which contained acceptable network error rate. To deal easily with ANN, a simple graphical user interface has been created. This ANN has been tested on a new sample. Results were compared with the actual results as well as the relationship of Solovev which is allocated to predict the strength cotton yarn. ANN has given more acceptable results than Solovev’s relationship.