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Research on underwear pressure prediction based on improved GA-BP algorithm

Research on underwear pressure prediction based on improved GA-BP algorithm For comfort evaluation of underwear pressure, this paper proposes an improved GA algorithm to optimize the weight and threshold of BP neural network, namely PSO-GA-BP neural network prediction model.Design/methodology/approachThe objective parameters of underwear, body shape data, skin deformation and other data are selected for simulation experiments to predict the objective pressure and subjective evaluation in dynamic and static state. Compared with the prediction results of BP neural network prediction model, GA-BP neural network prediction model and PSO-BP neural network prediction model, the performance of each prediction model is verified.FindingsThe results show that the BP neural network model optimized by PSO-GA algorithm can accelerate the convergence speed of the neural network and improve the prediction accuracy of underwear pressure.Originality/valuePSO-GA-BP model provides data support for underwear design, production and processing and has guiding significance for consumers to choose underwear. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Clothing Science and Technology Emerald Publishing

Research on underwear pressure prediction based on improved GA-BP algorithm

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References (43)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0955-6222
DOI
10.1108/ijcst-05-2020-0078
Publisher site
See Article on Publisher Site

Abstract

For comfort evaluation of underwear pressure, this paper proposes an improved GA algorithm to optimize the weight and threshold of BP neural network, namely PSO-GA-BP neural network prediction model.Design/methodology/approachThe objective parameters of underwear, body shape data, skin deformation and other data are selected for simulation experiments to predict the objective pressure and subjective evaluation in dynamic and static state. Compared with the prediction results of BP neural network prediction model, GA-BP neural network prediction model and PSO-BP neural network prediction model, the performance of each prediction model is verified.FindingsThe results show that the BP neural network model optimized by PSO-GA algorithm can accelerate the convergence speed of the neural network and improve the prediction accuracy of underwear pressure.Originality/valuePSO-GA-BP model provides data support for underwear design, production and processing and has guiding significance for consumers to choose underwear.

Journal

International Journal of Clothing Science and Technology – Emerald Publishing

Published: Jul 1, 2021

Keywords: Underwear pressure; Comfort evaluation; PSO-GA-BP; Objective pressure; Subjective evaluation

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