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http://dx.doi.org/10.5139/JKSAS.2006.34.1.049

Knowledge Discovery in Aerodynamic Design Space using Data Mining  

Jeong, Sin-Gyu (東北大學(JA))
, 동북대학교 (동북대학교)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.34, no.1, 2006 , pp. 49-55 More about this Journal
Abstract
Two data mining techniques, analysis of variance (ANOVA) and self-organizing map (SOM), are applied to knowledge discovery in aerodynamic design space. These methods make it possible to identify the effect of each design variable on the objective functions. Furthermore, ANOVA shows the effect of interaction between design variables on the objective function and SOM visualizes the trade-off among objective functions. Present methods are applied to the result of the supersonic wing design which includes 72 design variables and 4 objective functions.
Keywords
Data Mining; ANOVA; SOM;
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