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
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;
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
DOI :
10.1109/ICIEA.2007.4318431
