Artificial Neural Network-based Prediction Technique for Waterproofness of Seams Obtained by Using Fusible Threads

KARABAY G., ŞENOL Y., ÖZTÜRK H., Mesegul C.

Fibres and Textiles in Eastern Europe, cilt.151, sa.3, ss.27-32, 2022 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 151 Sayı: 3
  • Basım Tarihi: 2022
  • Doi Numarası: 10.2478/ftee-2022-0019
  • Dergi Adı: Fibres and Textiles in Eastern Europe
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.27-32
  • Anahtar Kelimeler: waterproof, seams, sewing threads, fusible threads, artificial neural network (ANN)
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

The aim of this study was to estimate waterproofness values of seams composed of the combination of fusible threads and antiwick sewing threads through artificial neural networks (ANN). Fusible threads were used to obtain waterproof seams for the first time. Therefore, estimating the value of the waterproofness variable with the help of models created from test values can contribute to accelerating the progress of further studies. Hence, ten different samples were prepared for two fabrics, and the waterproofness values of the seams obtained were tested using a Textest FX 3000 Hydrostatic Head Tester III. For the prediction of waterproofness values of the seams, the Levenberg-Marquardt backpropagation algorithm was used for artificial neural network pattern models with sigmoid and positive linear transfer functions. Finally, the ANN model was successful in estimating the waterproofness of the seams. The highest correlation coefficient was R = 0.95081 which indicated that the prediction made by the neural network model proved to be reliable.