Abstract
This article summarizes several analyses on employing an iterative learning method of the Computational Artificial Intelligence field, a Genetic Algorithm, focused on designing linear arrays. The objective of these analyses is the effectiveness improvement of these evolutive algorithms in this particular problem. The influence of giving certain values to each of the specific parameters of a Genetic Algorithm is characterized. Obtaining the optimal final solution depends on these parameter values. Thanks to this analysis, the Genetic Algorithm is optimized and also the best linear array geometry, based on certain established quality criteria, is found.
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© 2011 Springer-Verlag Berlin Heidelberg
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del Val, L. et al. (2011). Parameter Analysis of a Genetic Algorithm to Design Linear Array Geometries. In: Abraham, A., Corchado, J.M., González, S.R., De Paz Santana, J.F. (eds) International Symposium on Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 91. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19934-9_27
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DOI: https://doi.org/10.1007/978-3-642-19934-9_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19933-2
Online ISBN: 978-3-642-19934-9
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