Wavelet Network Based on Modified Auto-adapted Ant Colony Algorithm and Its Application

Author

Li, Guo ; Shan, Miyuan ; Wu, Juan

Author_Institution

Project Manage. & E-Commerce Lab., Hunan Univ., Changsha

Volume

1

fYear

0

fDate

0-0 0

Firstpage

2896

Lastpage

2900

Abstract

In order to solve the problems in wavelet network back propagation, such as low-precision, slow speed learning process and easy convergence to the local minimum points, ant colony algorithm was modified based on analyzing the fundamental of ant colony algorithm. Then a learning algorithm for wavelet network, which is modified auto-adapted ant colony algorithm, was put forward. An application example of customization product cost estimation was given at last. Learning process and precision of the algorithm is better than the others, which shows wavelet network training based on this algorithm has a better generalization ability and learning ability

Keywords

artificial life; costing; genetic algorithms; learning (artificial intelligence); neural nets; product customisation; wavelet transforms; autoadapted ant colony algorithm; cost estimation; customization product; generalization; genetic algorithm; learning algorithm; wavelet network backpropagation; Algorithm design and analysis; Automation; Convergence; Costs; Electronic mail; Genetic algorithms; Intelligent control; Laboratories; Project management; Wavelet analysis; ant colony algorithm; convengence speed; genetic algorithm; wavelet network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712895

Filename

1712895