Self-Organizing Map (SOM) has been applied to analyze 766 Pareto solutions obtained from the four-objective aerodynamic optimization of supersonic wings using Evolutionary Algorithms. Threedimensional Pareto front (tradeoff surface) is mapped onto the two-dimensional SOM where global tradeoffs are successfully visualized. Furthermore, from the clusters obtained in the SOM, the design variables are mapped onto another SOM. This leads to clusters of design variables which indicate the relative importance of design variables and their interactions. SOM is confirmed to be a versatile datamining tool for aeronautical engineering.
|出版ステータス||Published - 2002|
|イベント||40th AIAA Aerospace Sciences Meeting and Exhibit 2002 - Reno, NV, United States|
継続期間: 2002 1 14 → 2002 1 17
|Other||40th AIAA Aerospace Sciences Meeting and Exhibit 2002|
|Period||02/1/14 → 02/1/17|
ASJC Scopus subject areas