Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Fast clustering of male lower body based on GA-BP neural network

Fast clustering of male lower body based on GA-BP neural network The purpose of this paper is to improve the prediction accuracy of the body shape prediction model and provide some reference value for the design of underwear.Design/methodology/approachThe body size data of 250 male youths is measured to analyze the body shape of the lower body. And there is a total of 56 measurement items, which are clustered by GA-BP-K-means, K-means, optimal segmentation method for ordered samples, wavelet coefficient analysis, regression analysis and Naive Bayes Algorithm. Finally, a test male sample of an unknown body shape was clustered to verify the superiority of the GA-BP-K-means.FindingsThis paper presented the key factors for body shape clustering, and experimental results have shown that the GA-BP neural network model is higher in speed and precision than other algorithm prediction models.Originality/valueIt was clarified which is the key to body shape clustering. At the same time, the GA-BP-K-means algorithm can promote the popularization and application of the prediction model in body shape clustering. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Clothing Science and Technology Emerald Publishing

Fast clustering of male lower body based on GA-BP neural network

Download PDF
14 pages

Loading next page...
 
/lp/emerald-publishing/fast-clustering-of-male-lower-body-based-on-ga-bp-neural-network-aSX0m4Gh4r

References (23)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0955-6222
DOI
10.1108/ijcst-09-2018-0120
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to improve the prediction accuracy of the body shape prediction model and provide some reference value for the design of underwear.Design/methodology/approachThe body size data of 250 male youths is measured to analyze the body shape of the lower body. And there is a total of 56 measurement items, which are clustered by GA-BP-K-means, K-means, optimal segmentation method for ordered samples, wavelet coefficient analysis, regression analysis and Naive Bayes Algorithm. Finally, a test male sample of an unknown body shape was clustered to verify the superiority of the GA-BP-K-means.FindingsThis paper presented the key factors for body shape clustering, and experimental results have shown that the GA-BP neural network model is higher in speed and precision than other algorithm prediction models.Originality/valueIt was clarified which is the key to body shape clustering. At the same time, the GA-BP-K-means algorithm can promote the popularization and application of the prediction model in body shape clustering.

Journal

International Journal of Clothing Science and Technology – Emerald Publishing

Published: Apr 22, 2020

Keywords: Clustering; Male; GA-BP; K-means; Lower body

There are no references for this article.