Title :
An Application of Radial Basis Function Network and Genetic Algorithm to Fashion Design System
Author :
Yana Zhang ; Hua Yang
Author_Institution :
Shaanxi Polytech. Inst., Xian, China
Abstract :
In this paper, a genetic algorithm as well as a radial basis network has applied to solve the design problem of human fatigue. The hybrid method of neural network and genetic algorithm has been employed. The selected individuals from Genetic Algorithm are optimized and considered as value of nodes in the radial basis function networks neural network. The parameters of radial basis function network are optimized by K-Means combined with the value of similar distance. The fitness cost function of the genetic algorithm is approximated by artificial neural network. The performance of the method in fashion design verifies the effects of this method.
Keywords :
clothing industry; design engineering; ergonomics; genetic algorithms; production engineering computing; radial basis function networks; artificial neural network; design problem; fashion design system; genetic algorithm; human fatigue; k-means; radial basis function networks neural network; Approximation methods; Artificial neural networks; Clothing; Color; Fatigue; Genetic algorithms; Radial basis function networks; Analysis of public opinion; Heat value; Intelligence system; Micro-blogging;
Conference_Titel :
Intelligent Systems Design and Engineering Applications, 2013 Fourth International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4799-2791-3
DOI :
10.1109/ISDEA.2013.425
