Proposing a soft hybrid computing model to improve the prediction of the quality of seams in garments

For training the artifcial neural network to accurately predict a specifc parameter, several experimental results argenerally needed which makes it costly and time-consuming. Hence, there is a need for developing other methodthat can accurately predict based on a small number of experimental data. In this paper, a combination of artifcineural network and fuzzy regression methods was employed to develop a soft intelligent model for predicting thquality of seams in garments. The main idea of the proposed method is to simultaneously use the advantages of socomputing of fuzzy sets to achieve improved results from artifcial neural networks based on a relatively small experimental dataset. The results obtained from the proposed model showed its higher performance in comparison tits constituent models as well as other existing combinational methods.