Email this article Integrated evolutionary approachfor neural network ensembles automatic design
- Authors: Bukhtoyarov VV1, Semenkin ES1
-
Affiliations:
- Issue: Vol 11, No 3 (2010)
- Pages: 9-15
- Section: Articles
- Published: 15.03.2010
- URL: https://journals.eco-vector.com/2712-8970/article/view/508515
- ID: 508515
Cite item
Full Text
Abstract
New comprehensive approach for neural network ensemble design is proposed. It consists of method for neural networks automatic design and method for ensemble decision automatic construction. It is demonstrated that proposed approach is not less effective than other approaches for neural network ensemble design
About the authors
V V Bukhtoyarov
E S Semenkin
Email: saor_semenkin@sibsau.ru <mailto:saor_semenkin@sibsau.ru>
References
- Hansen L. K., Salamon P. Neural network ensembles // IEEE Trans. Pattern Analysis and Machine Intelligence. 1990. 12 (10). P. 993-1001.
- Cherkauer K. J. Human expert level performance on a scientific image analysis task by a system using combined artificial neural networks // Proc. AAAI-96 Workshop on Integrating Multiple Learned Models for Improving and Scaling Machine Learning Algorithms / by ed. P. Chan, S. Stolfo, D. Wolpert. Portland, OR: AAAI Press : Menlo Park, CA, 1996. P. 15-21.
- Hampshire J., Waibel A. A novel objective function for improved phoneme recognition using timedelay neural networks // IEEE Transactions on Neural Networks. 1990. № 1 (2). P. 216-228.
- Goldberg D. E. Genetic algorithms in search, optimization and machine learning. Reading, MA : Addison- Wesley, 1989.
- СеменкинЕ. ., СоповЕ. А. Вероятностные эвол-ционные алгоритмы оптимизации сложных систем // Тр. Междунар. науч.-прак. конф. AIS'05/CAD-2005. M. : Физматлит, 2005. С. 77-78.
- Perrone M. P., Cooper L. N. When networks disagree: ensemble method for neural networks // Artificial Neural Networks for Speech and Vision / by ed. R. J. Mammone. New York : Chapman & Hall, 1993. P. 126-142.
- Jimenez D. Dynamically weighted ensemble neural networks for classification // Proc. IJCNN-98. Vol. 1. Anchorage, AK : IEEE Computer Society Press : Los Alamitos, CA, 1998. P. 753-756.
- Zhou Z. H., Wu J., Tang W Ensembling neural networks: Many could be better than all // Artif. Intell. 2002. Vol. 137. № 1-2. P. 239-263.
- Koza J. R. The Genetic Programming Paradigm: Genetically Breeding Populations of Computer Programs to Solve Problems. Cambridge, MA : MIT Press, 1992.
- Yeh I-Ch. Modeling slump flow of concrete using second-order regressions and artificial neural networks // Cement and Concrete Composites. 2007. Vol. 29, № 6. P. 474-480.
Supplementary files
