Abstract
Multi-population particle swarm optimization (MPPSO) algorithm is proposed to train negatively correlated neural network ensemble. Each sub-swarm is responsible for training a component network. The architecture of each component neural network in the ensemble is automatically configured. The component networks are trained simultaneously and successively exchange information among them. Because our approach automatically determines the number of hidden units for the component neural networks, the rational architectures of the component network are achieved and hence the performance of ensemble is improved. The experimental results show that MPPSO for negatively correlated ensemble is an effective and practical method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hansen, L.K., Salamon, P.: Neural Network Ensembles. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-12, 993–1001 (1990)
Breiman, L.: Bagging Predictors. Machine Learning 24, 123–140 (1996)
Schapire, R.E.: The Strength of Weak Learnability. Machine Learning 5, 197–227 (1990)
Liu, Y., Yao, X.: Simultaneous Training of Negatively Correlated Neural Networks in an Ensemble. IEEE Transactions on Systems, Man and Cybernetics, Part B, 716–725 (1999)
Liu, Y., Yao, X., Higuchi, T.: Evolutionary Ensembles with Negative Correlation Learning. IEEE Transactions on Evolutionary Computation 4, 380–387 (2000)
Liu, Y., Qin, Z., Shi, Z., Chen, J.: Training Radial Basis Function Networks with Particle Swarms. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3173, pp. 317–322. Springer, Heidelberg (2004)
Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: Proceeding of IEEE International Conference on Neural Networks (ICNN 1995), Perth, Western Australia, vol. 4, pp. 1942–1947 (1995)
Blake, C., Merz, C.J.: UCI Repository of Machine Learning Databases (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Qin, Z., Liu, Y., Heng, X., Wang, X. (2005). Negatively Correlated Neural Network Ensemble with Multi-population Particle Swarm Optimization. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_83
Download citation
DOI: https://doi.org/10.1007/11427391_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25912-1
Online ISBN: 978-3-540-32065-4
eBook Packages: Computer ScienceComputer Science (R0)