@inbook{53d07e31b81641aca7cca98da2c3d641,
title = "Visualization and data mining of Pareto solutions using Self-Organizing Map",
abstract = "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.",
author = "Shigeru Obayashi and Daisuke Sasaki",
year = "2003",
doi = "10.1007/3-540-36970-8_56",
language = "English",
isbn = "3540018697",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "796--809",
editor = "Fonseca, {Carlos M.} and Fleming, {Peter J.} and Eckart Zitzler and Lothar Thiele and Kalyanmoy Deb",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}