Abstract
This paper proposes a new model called ACA-BP network. This network combines ant colony algorithm (ACA) with neural network and adopts ant colony algorithm to train authority value and threshold value of BP nerve network. It not only has the extensive mapping ability of neural network, but also has the advantages of high efficiency, rapid global convergence and distributed computation of ant system. The experiment result indicates the ACA-BP neural network outperforms the BP neural network.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Ge, Z., Sun, Z.: The Neural Network Theory and Matlab Application, pp. 324–327. Publishing House of Electronics Industry, Beijing (2008)
Schoonderwoerd, R., Holland, O., Bruten, J., et al: Ants for Load Balancing in Telecommunication Networks. Hewlett Packard Lab., Palo Alto, USA, Tech. Rep. HPL 1996, pp. 96–35 (1996)
Dorigo, M., Di Caro, G.: The ant colony optimization meta-heuristic, London, UK, pp. 11–32. McGraw Hill, New York (1982)
Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: optimization by a colony of cooperating agent. IEEE Transactions on Systerns, Man, and Cybemetics 26(1), 29–41 (1996)
Ruyun, C.: Research on the Application of BP Neural Networks. Control & Automation 23(8), 258–259 (2007)
Bonabeau, E., Dorigo, M., Theraulaz, G.: Inspiration for optimization from aocial insect behavior. Nature 406(6), 39–42 (2000)
Dorig, M.: Optimiztion, Learning and Natural Algorithma (in Italian). Ph.D. Dipartimento di Electronica, Politecnico di Milano, IT (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, Q., Shao, Y., Liu, Z. (2009). Research on ACA-BP Neural Network Model. In: Cai, Z., Li, Z., Kang, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2009. Communications in Computer and Information Science, vol 51. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04962-0_47
Download citation
DOI: https://doi.org/10.1007/978-3-642-04962-0_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04961-3
Online ISBN: 978-3-642-04962-0
eBook Packages: Computer ScienceComputer Science (R0)