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Self-Learning Metamodels for Optimization

Academic Article
Publication Date:
2009
abstract:
The paper discusses strategies for metamodels in optimization problems involving expensive high-delity analysis tools. A strategy to assess the accuracy of the metamodels and to increase their completeness and delity during the optimization process is suggested and evaluated.
Iris type:
01.01 Articolo in rivista
Keywords:
Simulation based design; Shape optimization; Derivative-free optimization; Variable fidelity
List of contributors:
Peri, Daniele
Authors of the University:
PERI DANIELE
Handle:
https://iris.cnr.it/handle/20.500.14243/161093
Published in:
SHIP TECHNOLOGY RESEARCH
Journal
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