Abstract
In this paper we present an evolutionary method to create an interpretable modular system. It consists of many neuro-fuzzy structures which are merged using a very popular algorithm called AdaBoost. As the alternative to the backpropagation method to train all models a special evolutionary algorithm has been used based on the evolutionary strategy (μ, λ). © 2008 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Korytkowski, M., Gabryel, M., Rutkowski, L., & Drozda, S. (2008). Evolutionary methods to create interpretable modular system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5097 LNAI, pp. 405–413). Springer Verlag. https://doi.org/10.1007/978-3-540-69731-2_40
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