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2000
Volume 1, Issue 1
  • ISSN: 2666-2949
  • E-ISSN: 2666-2957

Abstract

Fabric is one of the keys and vital design factors in fashion design. However, the selection of relevant fabrics is rather complex for designers and managers due to the complexity of criteria at different levels.

In this paper, we propose a new fabric recommendation model in order to quickly realize fabric selection from non-technical fashion features only and predict fashion features from any fabric’s technical parameters. This approach is extremely significant for fashion designers who do not completely master fabric technical details. It is also very useful for fabric developers who have no knowledge on fashion markets and fashion consumers.

The proposed fabric recommendation model has been built by exploiting designers’ professional knowledge and consumers’ preferences. Concretely, we first use fuzzy sets for formalizing and interpreting measured technical parameters and linguistic sensory properties of fabrics and then model the relation between the technical parameters and sensory properties by using rough sets. Next, we model the relation between fashion themes and sensory properties using fuzzy relations. By combining these two models, we establish a hybrid model characterizing the relation between fashion themes and technical parameters.

The proposed model has been validated through a real fabric recommendation case for designer’s specific requirements. We can find that the proposed model is efficient since the averaged value of prediction errors is 8.57%, which does not exceed 10% (generally considered as an allowable range of human perception error).

The proposed model will constitute one important component for establishing an intelligent recommender system for garment design, enabling to support innovations in textile/apparel industry in terms of mass customization and e-shopping.

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/content/journals/flme/10.2174/2666294901666210223165824
2022-04-01
2024-11-22
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References

  1. KarthikeyanB. SztanderaL.M. Analysis of tactile perceptions of textile materials using artificial intelligence techniques Part 1: for-ward engineering.Int. J. Cloth. Sci. Technol.20102218720110.1108/09556221011018658
    [Google Scholar]
  2. AllerkampD. "Tactile perception of textiles in a virtual-reality system",Springer Publishing Company201010.1007/978‑3‑642‑13974‑1
    [Google Scholar]
  3. RamalhoA. SzekeresP. FernandesE. Friction and tactile perception of textile fabrics.Tribol. Int.201363293310.1016/j.triboint.2012.08.018
    [Google Scholar]
  4. HanQ.Y. LiY.M. JuF. The optimum choice of fabric based on analytic hierarchy process.Adv. Mat. Res.2014104816817210.4028/www.scientific.net/AMR.1048.168
    [Google Scholar]
  5. McCannJ. Environmentally conscious fabric selection in sportswear design.Textiles for Sportswear.R. Shishoo Ed. Woodhead Publishing Ltd.20151752
    [Google Scholar]
  6. NematiS. "Decision making on the optimised choice of pneumatic formwork textile for foam-filled structural composite panels".Int. J. Geomate201710.21660/2017.39.7350
    [Google Scholar]
  7. MojsovK. "Enzymatic scouring and bleaching of cotton terry fabrics - opportunity of the improvement on some physicochemical and mechanical properties of the fabrics"201815740751
    [Google Scholar]
  8. ChakrabortyS. ChatterjeeP. Cotton fabric selection using a grey fuzzy relational analysis approach.J. Inst. Eng. India Ser.20191002136
    [Google Scholar]
  9. ZakharkevichO. ZhylenkoT. KoshevkoY. "Expert System to Select The Fabrics for Transformable Garments".Vlakna A Texti201825105112
    [Google Scholar]
  10. ZhangZ. TangX. WangY. LiJ. TianM. XiaoP. Effect of fiber type, water content, and velocity on wetness perception by the volar forearm test: Stimulus Intensity Test.Perception201948986288110.1177/0301006619863264 31337268
    [Google Scholar]
  11. WangJ. ShiK. WangL. An objective fabric smoothness assessment method based on a multi-scale spatial masking model.Vol. PP201911
    [Google Scholar]
  12. WangL.J.B. "Contribution to development of an intelligent system for supporting personalized fashion design"20121914801486
    [Google Scholar]
  13. SaitoS. "Semantic differential method".Japanese J. Ergono201014
    [Google Scholar]
  14. ZadehL.A. KacprzykJ. Computing with words in information/intelligent systems 1.Stud. Fuzziness Soft Computing19993322125210.1007/978‑3‑7908‑1873‑4
    [Google Scholar]
  15. DongM. ZengX. KoehlL. An interactive knowledge-based recommender system for fashion product design in the big data envi-ronment.Inf. Sci.202054046948810.1016/j.ins.2020.05.094
    [Google Scholar]
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  • Article Type:
    Research Article
Keyword(s): Fashion design; fashion theme; fuzzy logic; garment design; rough sets; sensory evaluation
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