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

@inproceedings{Obayashi2003VisualizationAD,
  title={Visualization and Data Mining of Pareto Solutions Using Self-Organizing Map},
  author={Shigeru Obayashi and Daisuke Sasaki},
  booktitle={EMO},
  year={2003}
}
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… CONTINUE READING
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