The paper discusses strategies for metamodels in optimization problems involving expensive high-fidelity analysis tools. A strategy to assess the accuracy of the metamodels and to increase their completeness and fidelity during the optimization process is suggested and evaluated.


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    Title :

    Self-Learning Metamodels for Optimization


    Contributors:

    Published in:

    Ship Technology Research ; 56 , 3 ; 95-109


    Publication date :

    2009-07-01


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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