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Prediction of the tactile comfort of fabrics from functional finishing parameters using fuzzy logic and artificial neural network models
University of Borås, Faculty of Textiles, Engineering and Business. (Textile Materials Technology)ORCID iD: 0000-0002-0781-319X
Faculty of Textiles, Leather and Industrial Management, ‘Gheorghe Asachi’ Technical University of Iasi.
Faculty of Textiles, Leather and Industrial Management, ‘Gheorghe Asachi’ Technical University of Iasi.
College of Textile and Clothing Engineering, Soochow University.
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2019 (English)In: Textile research journal, ISSN 0040-5175, E-ISSN 1746-7748Article in journal (Refereed) Published
Sustainable development
According to the author(s), the content of this publication falls within the area of sustainable development.
Abstract [en]

This paper aims to predict the hand values (HVs) and total hand values (THVs) of functional fabrics by applying the fuzzy logic model (FLM) and artificial neural network (ANN) model. Functional fabrics were evaluated by trained panels employing subjective evaluation scenarios. Firstly, the FLM was applied to predict the HV from finishing parameters; then, the FLM and ANN model was applied to predict the THV from the HV. The estimation of the FLM on the HV was efficient, as demonstrated by the root mean square error (RMSE) and relative mean percentage error (RMPE); low values were recorded, except those bipolar descriptors whose values are within the lowermost extreme values on the fuzzy model. However, the prediction performance of the FLM and ANN model on THV was effective, where RMSE values of0.21 and 0.13 were obtained, respectively; both values were within the variations of the experiment. The RMPEvalues for both models were less than 10%, indicating that both models are robust, effective, and could be utilized in predicting the THVs of the functional fabrics with very good accuracy. These findings can be judiciously utilized for the selection of suitable engineering specifications and finishing parameters of functional fabrics to attain define tactile comfort properties, as both models were validated using real data obtained by the subjective evaluation of functional fabrics.

Place, publisher, year, edition, pages
UK: Sage Publications, 2019.
Keywords [en]
fuzzy logic, hand prediction, total hand value, hand value, trained panels, artificial neural network
National Category
Engineering and Technology
Research subject
Textiles and Fashion (General)
Identifiers
URN: urn:nbn:se:hb:diva-15828DOI: 10.1177/0040517519829008OAI: oai:DiVA.org:hb-15828DiVA, id: diva2:1291682
Projects
Quality inspection and evaluation of functional or smart textile fabric surface by skin contact mechanicsAvailable from: 2019-02-26 Created: 2019-02-26 Last updated: 2019-02-27Bibliographically approved

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