Self-organizing map of pareto solutions obtained from multiobjective supersonic wing design

Shigeru Obayashi; Daisuke Sasaki

Self-organizing map of pareto solutions obtained from multiobjective supersonic wing design

Shigeru Obayashi, Daisuke Sasaki

IFS - Creative Flow Research Division

Tohoku University

Research output: Contribution to conference › Paper › peer-review

8 Citations (Scopus)

Abstract

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.

Original language	English
Publication status	Published - 2002
Event	40th AIAA Aerospace Sciences Meeting and Exhibit 2002 - Reno, NV, United States Duration: 2002 Jan 14 → 2002 Jan 17

Conference

Conference	40th AIAA Aerospace Sciences Meeting and Exhibit 2002
Country/Territory	United States
City	Reno, NV
Period	02/1/14 → 02/1/17

Cite this

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title = "Self-organizing map of pareto solutions obtained from multiobjective supersonic wing design",

abstract = "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.",

author = "Shigeru Obayashi and Daisuke Sasaki",

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AU - Obayashi, Shigeru

AU - Sasaki, Daisuke

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AB - 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.

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T2 - 40th AIAA Aerospace Sciences Meeting and Exhibit 2002

Y2 - 14 January 2002 through 17 January 2002

ER -

Self-organizing map of pareto solutions obtained from multiobjective supersonic wing design

Abstract

Conference

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