Weight Analysis of Brassiere-wearing Influence Factors Based on Neural Network

被引：0

作者：

Chen, Min-Zhi ^{[1
]}

Zhang, Wei-Yuan ^{[1
]}

He, Ying ^{[2
]}

Jing, Yan-Ping ^{[2
]}

机构：

[1] DongHua Univ, Dept Fash Design & Engn, Shanghai, Peoples R China

[2] Zhejiang Sci Tech Univ, Sch Fash Design & Engn, Hangzhou, Peoples R China

来源：

2009 INTERNATIONAL CONFERENCE ON INDUSTRIAL MECHATRONICS AND AUTOMATION | 2009年

关键词：

brassiere-wearing; neural network; sensitivity analysis; weight;

D O I：

10.1109/ICIMA.2009.5156605

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The brassiere-wearing effect is produced by the combined action of body shape and brassiere. The process is so complicated that it is an issue for people to realize what functions the different factors perform in the change of bust appearance. In this research, an artificial neural network model was applied, in which the input neurons contained I I possible factors including body measurements and brassiere configuration data. The model consisted of 6 BP neural networks. Each of them could simulate and predict one effect parameter respectively. Based on them, the sensitivity analysis was adopted to achieve the weight distributions of the influence factors for each of the effect parameters. Through the weight analysis, the influence of all the factors in brassiere-wearing became clear. The result would help fashion designers to design brassiere pertinently, according to the individual body shape and special need of wearing effect.

引用

页码：241 / +

页数：2