JOURNAL OF THE TEXTILE INSTITUTE, vol.115, no.5, pp.757-767, 2024 (SCI-Expanded)
Denim is a special fabric preferred by all segments of society. Many production factors affect the properties, performance levels and quality of denim products. In today’s textile manufacturing management, quality parameter prediction is very important. In the context of this work, a new prediction
model has been introduced for calculating denim fabric quality parameters. The meta-heuristic combination of Artificial Neural Network (ANN) and Artificial Bee Colony (ABC) algorithm is the proposed
in this study. The proposed hybrid model was evaluated using data on production parameters
acquired from a significant Turkish manufacturer of denim fabric. The denim fabric quality parameters
results obtained from the ANN and the proposed ANN based ABC (ABC-ANN) algorithms were compared with the results of all models on test data. The performances of the measured quality values
were evaluated and compared in terms of Mean Absolute Percentage Error (MAPE), Root Mean
Squared Error (RMSE), and Receiver Operating Characteristic (ROC) curve analysis. According to the
comparison results, the proposed ANN-based ABC algorithm is superior in predicting the mechanical
properties of denim fabric from the production parameters.