320 Application of Fuzzy Decision Tree to Datasets Obtained by Evolutionary Algorithms (EAs)
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In this paper, the effectiveness of the Fuzzy Decision Tree as a data mining technique for datasets obtained by Evolutionary Algorithms, which is a preferred optimization technique for multi-objective problems, is investigated. The Fuzzy Decision Tree is constructed to evaluate the influence of design variables on the objective functions. Based on the results of the Fuzzy Decision Tree, designers can reduce the number of design variables and focus on the important design variables. The technique is applied to the aerodynamic optimization of a supersonic wing design which has four objective functions and 72 design variables.
