The Use of Artificial Neural Networks to Estimate Thermal Resistance of Knitted Fabrics

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24410%2F15%3A00003200" target="_blank" >RIV/46747885:24410/15:00003200 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
The Use of Artificial Neural Networks to Estimate Thermal Resistance of Knitted Fabrics
Original language description
This study aims to develop a model for the prediction of thermal resistance of fleece fabric by using regression analysis and artificial neural network technique. Primarily fleece fabrics protect human body from heat loss during cold weather. Its secondpurpose is to absorb sweat from human skin. Fleece fabric is commonly used to make sweatshirts, trousers, and jackets for cold weather. Higher thermal resistance of fleece is one of the main demands of users. Many factors can influence the thermal resistance efficiency of fleece. We have used porosity, thickness of fabric, thermal conductivity of fabric, overall moisture management capacity, thermal absorptivity, percentage of cotton, and polyester and planner weight as independent variables for the prediction of thermal resistance of fleece fabric. We have found that there was a significant difference between regression and artificial neural network analysis in the selection of most significant factor. Nevertheless, both models are sig
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JJ - Other materials
OECD FORD branch
—

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)