DocumentCode
3441693
Title
Design Optimization Based on Neural Networks And Ant Colony Optimization
Author
Guo, Wu Yu ; Zhi, Song Chong
Author_Institution
AnHui Univ. of Technol., Maanshan
fYear
2007
fDate
23-25 May 2007
Firstpage
360
Lastpage
362
Abstract
In order to raise the design efficiency and get the most excellent design effect, this paper combined ant colony optimization (ACO) algorithm and neural networks, which based on ACO algorithm and the implementing framework of ACO. It gives the basic theory and steps; The test results show that rapid global convergence and reached the lesser mean square error(MSE) when compared with genetic algorithm, simulated annealing algorithm, the BP algorithm with momentum term.
Keywords
neural nets; optimisation; ant colony optimization; design optimization; genetic algorithm; mean square error; neural networks; rapid global convergence; simulated annealing algorithm; Ant colony optimization; Design optimization; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4244-0737-8
Electronic_ISBN
978-1-4244-0737-8
Type
conf
DOI
10.1109/ICIEA.2007.4318431
Filename
4318431
Link To Document