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Special Topics & Reviews in Porous Media: An International Journal
ESCI SJR: 0.259 SNIP: 0.466 CiteScore™: 0.83

ISSN Print: 2151-4798
ISSN Online: 2151-562X

Special Topics & Reviews in Porous Media: An International Journal

DOI: 10.1615/SpecialTopicsRevPorousMedia.v3.i1.40
pages 35-53

A NEURAL NETWORK SYSTEM FOR PREDICTION OF THERMAL RESISTANCE OF KNIT FABRICS

Hamza Alibi
LESTE, ENIM Avenue IBN ELJAZZAR, 5019 Monastir, Tunisia
Faten Fayala
Laboratoire d'Etudes des Systèmes Thermiques et Energétiques; and Département de Génie Textile, Ecole Nationale d'Ingénieurs de Monastir, (E.N.I.M), 5019 Monastir, Tunisie
Abdelmajid Jemni
Laboratoire d'Etudes des Systèmes Thermiques et Energétiques, Ecole Nationale d'Ingénieurs de Monastir, University of Monastir, Avenue Ibn El Jazzar, 5019, Monastir, Tunisie
Xianyi Zeng
Laboratoire GEMTEX ENSAIT de Roubaix, Avenue de l'Hermitage Roubaix Cedex, France

ABSTRACT

An artificial neural network (ANN) was developed to predict the thermal resistance of knit fabrics. Thickness, porosity, air permeability, weight per unit area, and fiber conductivity were taken as input variables of the ANN. Data on thermal resistance were measured on experiments carried out on jersey knitted structures. An original (virtual leave-one-out) approach dealing with the overfitting phenomenon and allowing the selection of the optimal neural network architecture was used. The optimal ANN model contained three hidden neurons in the hidden layer. This model was validated by testing data, and the confidence intervals on the predictions were evaluated. It shows good performance in prediction with better accuracy. The developed neural model is expected to be used for a wide industrial context.


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