Data mining of non-dominated solutions using proper orthogonal decomposition

Akira Oyama; Taku Nonomura; Kozo Fujii

doi:10.1145/1569901.1570245

Data mining of non-dominated solutions using proper orthogonal decomposition

Akira Oyama, Taku Nonomura, Kozo Fujii

ENG - Aerospace Engineering

JAXA Institute of Space and Astronautical Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

A new approach to extract useful design information from non-dominated solutions of real-world multiobjective optimization problems is proposed. The proposed approach enables an analysis of line, face, or volume data that Pareto-optimal solutions have such as flow field and stress distribution by decomposing the data into principal modes using proper orthogonal decomposition. Analysis of the shape and surface pressure data of the non-dominated solutions of an aerodynamic transonic airfoil shape optimization problem shows capability of the proposed approach for design knowledge extraction for real-world design optimization problems.

Original language	English
Title of host publication	Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Pages	1935-1936
Number of pages	2
DOIs	https://doi.org/10.1145/1569901.1570245
Publication status	Published - 2009
Event	11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 - Montreal, QC, Canada Duration: 2009 Jul 8 → 2009 Jul 12

Publication series

Name	Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009

Conference

Conference	11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Country/Territory	Canada
City	Montreal, QC
Period	09/7/8 → 09/7/12

Keywords

Data mining
Multi-objective evolutionary algorithm
Real world application

Access to Document

10.1145/1569901.1570245

Cite this

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title = "Data mining of non-dominated solutions using proper orthogonal decomposition",

abstract = "A new approach to extract useful design information from non-dominated solutions of real-world multiobjective optimization problems is proposed. The proposed approach enables an analysis of line, face, or volume data that Pareto-optimal solutions have such as flow field and stress distribution by decomposing the data into principal modes using proper orthogonal decomposition. Analysis of the shape and surface pressure data of the non-dominated solutions of an aerodynamic transonic airfoil shape optimization problem shows capability of the proposed approach for design knowledge extraction for real-world design optimization problems.",

keywords = "Data mining, Multi-objective evolutionary algorithm, Real world application",

author = "Akira Oyama and Taku Nonomura and Kozo Fujii",

year = "2009",

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language = "English",

isbn = "9781605583259",

series = "Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009",

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note = "11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 ; Conference date: 08-07-2009 Through 12-07-2009",

}

Oyama, A, Nonomura, T & Fujii, K 2009, Data mining of non-dominated solutions using proper orthogonal decomposition. in Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009. Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, pp. 1935-1936, 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, Montreal, QC, Canada, 09/7/8. https://doi.org/10.1145/1569901.1570245

Data mining of non-dominated solutions using proper orthogonal decomposition. / Oyama, Akira; Nonomura, Taku; Fujii, Kozo.
Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009. 2009. p. 1935-1936 (Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Data mining of non-dominated solutions using proper orthogonal decomposition

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AU - Nonomura, Taku

AU - Fujii, Kozo

PY - 2009

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N2 - A new approach to extract useful design information from non-dominated solutions of real-world multiobjective optimization problems is proposed. The proposed approach enables an analysis of line, face, or volume data that Pareto-optimal solutions have such as flow field and stress distribution by decomposing the data into principal modes using proper orthogonal decomposition. Analysis of the shape and surface pressure data of the non-dominated solutions of an aerodynamic transonic airfoil shape optimization problem shows capability of the proposed approach for design knowledge extraction for real-world design optimization problems.

AB - A new approach to extract useful design information from non-dominated solutions of real-world multiobjective optimization problems is proposed. The proposed approach enables an analysis of line, face, or volume data that Pareto-optimal solutions have such as flow field and stress distribution by decomposing the data into principal modes using proper orthogonal decomposition. Analysis of the shape and surface pressure data of the non-dominated solutions of an aerodynamic transonic airfoil shape optimization problem shows capability of the proposed approach for design knowledge extraction for real-world design optimization problems.

KW - Data mining

KW - Multi-objective evolutionary algorithm

KW - Real world application

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T3 - Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009

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BT - Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009

T2 - 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009

Y2 - 8 July 2009 through 12 July 2009

ER -

Data mining of non-dominated solutions using proper orthogonal decomposition

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Keywords

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