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2003
Springer

Visualization and Data Mining of Pareto Solutions Using Self-Organizing Map

9 years 5 months ago
Visualization and Data Mining of Pareto Solutions Using Self-Organizing Map
Self-Organizing Maps (SOMs) have been used to visualize tradeoffs of Pareto solutions in the objective function space for engineering design obtained by Evolutionary Computation. Furthermore, based on the codebook vectors of cluster-averaged values of respective design variables obtained from the SOM, the design variable space is mapped onto another SOM. The resulting SOM generates clusters of design variables, which indicate roles of the design variables for design improvements and tradeoffs. These processes can be considered as data mining of the engineering design. Data mining examples are given for supersonic wing design and supersonic wing-fuselage design.
Shigeru Obayashi, Daisuke Sasaki
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where EMO
Authors Shigeru Obayashi, Daisuke Sasaki
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