Neural Network for Predicting Thermal Conductivity of Knit Materials

  • Fayala F
  • Alibi H
  • Benltoufa S
  • et al.
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Abstract

The major aim of comfort research is to find the comfort temperature for an individual or group. This subjective property can be evaluated by means of thermal conductivity as a physical characteristic of fabric. This phenomenon depends on many fabric parameters and it is difficult to study the effect of ones without changing the others. In addition, the non-linear relationship of fabric parameters and thermal conductivity handicap mathematical modelling. So a neural network approach was used to predict the thermal conductivity of knitting structure as a function of porosity, air permeability, weight and fiber conductivity. Data on thermal conductivity are measured by experiments carried out on jersey knitted structure.

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Fayala, F., Alibi, H., Benltoufa, S., & Jemni, A. (2008). Neural Network for Predicting Thermal Conductivity of Knit Materials. Journal of Engineered Fibers and Fabrics, 3(4), 155892500800300. https://doi.org/10.1177/155892500800300407

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