By Topic

Research and application of genetic algorithm-based optimized radial basis neural network model parameter design

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Xiujuan Fan ; Beijing Inst. of Fashion Technol., Beijing, China

In this paper, the structural features of the radial basis network as well as both the center value of the hidden node and the width parameter's influence on the structure are analyzed; the strategy of optimizing the center value and the width parameter by genetic algorithm is researched. An above-algorithm based yarn quality forecast model is established, and the result shows that the predictive output of the model basically matches with the actually measured sample, and the network trained is capable of fast and accurately predict the quality indexes.

Published in:

Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on

Date of Conference:

16-19 Aug. 2009