Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/39257
Title: A review of literature about the use of artificial neural networks systems on prediction of clothing comfort
Other Titles: Giyim konforunun tahminlenmesinde yapay sinir ağları sistemlerinin kullanımına yönelik bir literatür araştırması
Authors: Utkun, Emine
Keywords: Clothing comfort; Artificial neural networks; Textile sektoru
Publisher: PAMUKKALE UNIV
Abstract: In recent years, with the increasing of consumers' expectations from textile products, researchers and producers of textile and apparel sectors focused on development of comfortable clothing systems. Artificial neural networks systems are research techniques that are trying to contribute to these developments.
There are a lot of researches in literature about analysing relationship between clothing comfort and parameters of fabrics using statistical methods. On the other hand, there are some limitations in using them. One of the most common problems encountered in statistical modelling is non-linear relationship between clothing comfort and the parameters of fabrics. Artificial neural networks systems are known trying to make prediction considering all the impact of the parameters together.
In this study, a literature research was performed about using artificial neural networks in prediction of clothing comfort.
URI: https://hdl.handle.net/11499/39257
https://doi.org/10.5505/pajes.2014.29491
ISSN: 1300-7009
Appears in Collections:Buldan Meslek Yüksekokulu Koleksiyonu
TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File SizeFormat 
e82540ba-e381-457a-8cde-ec1ba6cb7611.pdf744.17 kBAdobe PDFView/Open
Show full item record



CORE Recommender

WEB OF SCIENCETM
Citations

1
checked on Dec 19, 2024

Page view(s)

62
checked on Aug 24, 2024

Download(s)

14
checked on Aug 24, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.