Predicting quality parameters of denim fabrics using developed ANN based Artificial Bee Colony algorithm

Katırcıoğlu G., Aydoğan E. K., Delice Y., Akgül E.

JOURNAL OF THE TEXTILE INSTITUTE, ss.1-11, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1080/00405000.2023.2201560
  • Dergi Adı: JOURNAL OF THE TEXTILE INSTITUTE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, INSPEC
  • Sayfa Sayıları: ss.1-11
  • Kayseri Üniversitesi Adresli: Evet

Özet

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.