Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Tactile Comfort Prediction of Functional Fabrics from Instrumental Data Using Intelligence Systems
University of Borås, Faculty of Textiles, Engineering and Business. Faculty of Textiles, Leather & Industrial Management. (Textile Materials Technology)ORCID iD: 0000-0002-0781-319X
The College of Textile and Clothing Engineering, Soochow University.
The College of Textile and Clothing Engineering, Soochow University.
University of Borås, Faculty of Textiles, Engineering and Business. (Textile Materials Technology)ORCID iD: 0000-0002-4369-9304
Show others and affiliations
2019 (English)In: Fibers And Polymers, ISSN 1229-9197, E-ISSN 1875-0052, Vol. 20, no 1, p. 199-209Article 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]

Subjective and objective evaluations of the handle of textile materials are very important to describe its tactile comfort for next-to-skin goods. In this paper, the applicability of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) modeling approaches for the prediction of the psychological perceptions of functional fabrics from mechanical properties were investigated. Six distinct functional fabrics were evaluated using human subjects for their tactile score and total hand values (THV) using tactile and comfort-based fabric touch attributes. Then, the measurement of mechanical properties of the same set of samples using KES-FB was performed. The RMSE values for ANN and ANFIS predictions were 0.014 and 0.0122 and are extremely lower than the variations of the perception scores of 0.644 and 0.85 forANN and ANFIS, respectively with fewer prediction errors. The observed results indicated that the predicted tactile score and are almost very close to the actual output obtained using human judgment. Fabric objective measurement-technology, therefore, provides reliable measurement approaches for functional fabric quality inspection, control, and design specification.

Place, publisher, year, edition, pages
Korea: Springer, 2019. Vol. 20, no 1, p. 199-209
Keywords [en]
ANFIS, ANN, Mechanical properties, Total hand value, Tactile comfort
National Category
Engineering and Technology
Research subject
Textiles and Fashion (General)
Identifiers
URN: urn:nbn:se:hb:diva-15829DOI: 10.1007/s12221-019-8301-9Scopus ID: 2-s2.0-85061661992OAI: oai:DiVA.org:hb-15829DiVA, id: diva2:1291821
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

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Tadesse, Melkie GetnetNierstrasz, Vincent

Search in DiVA

By author/editor
Tadesse, Melkie GetnetNierstrasz, Vincent
By organisation
Faculty of Textiles, Engineering and Business
In the same journal
Fibers And Polymers
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 41 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf