DocumentCode
3034937
Title
Study of modern industria product optimization design based on image
Author
Wei, Jiang Hua
Author_Institution
Coll. of Inf. Sci. & Eng, Henan Univ. of Technol., Zhengzhou, China
fYear
2011
fDate
26-28 July 2011
Firstpage
5546
Lastpage
5549
Abstract
To design the acceptable products that meet consumer emotional demands is very important, and a novel method is proposed combiningg neural network with genetic algorithm(GA). In this paper, a back propagation neural network(BPNN) is applied to map the relationships between product design elements and customer kansei image evaluation. And then, GA is employed to search for the optimal product form which satisfies customer requirement by using the trained neural network. In the end, the framework of product image form optimization design system using Virtual Reality Modeling Language(VRML) is analyzed. To test the method, an example of kettle design is used to study, the results show that this method is valid and feasible.
Keywords
backpropagation; genetic algorithms; neural nets; product design; virtual reality languages; VRML; back propagation neural network; consumer emotional demand; customer kansei image evaluation; customer requirement; genetic algorithm; kettle design; modern industrial product optimization design; optimal product; product image; trained neural network; virtual reality modeling language; Biological cells; Genetic algorithms; Image color analysis; Object oriented modeling; Optimization; Product design; Solid modeling; back propagation neural network; genetic algorithme; optimization design; product design;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Technology (ICMT), 2011 International Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-61284-771-9
Type
conf
DOI
10.1109/ICMT.2011.6002317
Filename
6002317
Link To Document