Abstract
In this paper, we propose an overall architecture for hardware implementation of genetic algorithms. The proposed architecture is independent of such specifics. It implements the fitness computation using a neural networks. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
APA
Nedjah, N., & De Macedo Mourelle, L. (2005). Hardware architecture for genetic algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3533 LNAI, pp. 554–556). Springer Verlag. https://doi.org/10.1007/11504894_76
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