• DocumentCode
    239414
  • Title

    A proposal on analysis support system based on association rule analysis for non-dominated solutions

  • Author

    Watanabe, Shigetaka ; Chiba, Ryosuke ; Kanazaki, Masahiro

  • Author_Institution
    Coll. of Inf. & Syst., Muroran Inst. of Technol., Muroran, Japan
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    880
  • Lastpage
    887
  • Abstract
    This paper presents a new analysis support system for analyzing non-dominated solutions (NDSs) derived by evolutionary multi-criterion optimization (EMO). The main features of the proposed system are to use association rule analysis and to perform a multi-granularity analysis based on a hierarchical tree of NDSs. The proposed system applies association rule analysis to the whole NDSs and derives association rules related to NDSs. And a hierarchical tree is created through our original association rule grouping that guarantees to keep at least one common features. Each node of a hierarchical tree corresponds to one group consisting of association rules and is fixed in position according to inclusion relations between nodes. Since each node has some kinds of common features, the designer can analyze each node with previous knowledge of these common features. To investigate the characteristics and effectiveness of the proposed system, the proposed system is applied to the concept design problem of hybrid rocket engine (HRE) which has two objectives and six variable parameters. HRE separately stores two different types of thrust propellant unlike in the case of usual other rockets and the concept design problem of HRE has been provided by JAXA. The results of this application provided possible to analyze the trends and specifics contained in NDSs in an organized way unlike analysis approaches targeted at the whole NDSs.
  • Keywords
    aerospace computing; data mining; evolutionary computation; propellants; rockets; trees (mathematics); EMO; HRE; JAXA; NDSs; analysis support system; association rule analysis; association rule grouping; concept design problem; evolutionary multicriterion optimization; hierarchical tree; hybrid rocket engine; inclusion relations; multigranularity analysis; nondominated solutions; thrust propellant; variable parameters; Association rules; Data visualization; Engines; Feature extraction; Market research; Optimization; Rockets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2014 IEEE Congress on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6626-4
  • Type

    conf

  • DOI
    10.1109/CEC.2014.6900650
  • Filename
    6900650