Abstract
In Multilevel Optimization there is usually a choice to be made between different models when carrying out design evaluations. The choice is between accurate / computationally expensive evaluations and approximate/ computational cheap ones. Here, a strategy is sought for selecting between different models during the search. The focus of the paper is on preliminary work carried out using a self organizing map (SOM) for model selection.
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El-Beltagy, M., Keane, A. (1999). Using Self Organizing Maps and Genetic Algorithms for Model Selection in Multilevel Optimization. In: Imam, I., Kodratoff, Y., El-Dessouki, A., Ali, M. (eds) Multiple Approaches to Intelligent Systems. IEA/AIE 1999. Lecture Notes in Computer Science(), vol 1611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48765-4_17
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DOI: https://doi.org/10.1007/978-3-540-48765-4_17
Publisher Name: Springer, Berlin, Heidelberg
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