Abstract
This paper gives an overview of how visualization techniques can help us to improve an evolutionary algorithm that trains artificial neural networks. Kohonen’s self-organizing maps (SOM) are used for multidimensional scaling and projection of high dimensional search spaces. The SOM visualization technique used here makes visualization of the evolution process easy and intuitive.
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Romero, G., Arenas, M., Castillo, P., Merelo, J. (2003). Visualization of Neural Net Evolution. In: Mira, J., Álvarez, J.R. (eds) Computational Methods in Neural Modeling. IWANN 2003. Lecture Notes in Computer Science, vol 2686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44868-3_68
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DOI: https://doi.org/10.1007/3-540-44868-3_68
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