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Interval GA for evolving neural networks with interval weights and biases.
- Source :
- 2012 Proceedings of SICE Annual Conference (SICE); 1/ 1/2012, p1542-1545, 4p
- Publication Year :
- 2012
-
Abstract
- In this paper, we propose an extension of genetic algorithm for neuroevolution of interval-valued neural networks. In the proposed GA, values in the genotypes are not real numbers but intervals. We apply our interval-valued GA (IvGA) to the approximate modeling of interval functions with interval-valued neural networks. Experimental results showed that INNs trained by our IvGA approximated a test function to a certain extent, despite the fact that the learning was not supervised. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISBNs :
- 9781467322591
- Database :
- Complementary Index
- Journal :
- 2012 Proceedings of SICE Annual Conference (SICE)
- Publication Type :
- Conference
- Accession number :
- 86590950