Minimal Function Calls Approach with On-Line Learning and Dynamic Weighting for Computationally Intensive Design Optimisation
Sykulski, J.K., Al-Khoury, A.H. and Goddard, K.F. (2000) Minimal Function Calls Approach with On-Line Learning and Dynamic Weighting for Computationally Intensive Design Optimisation.
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Design/optimisation processes requiring intensive finite-element computation can be made significantly more efficient, while preserving good accuracy, by combining the Response Surface Methodology with on-line learning and dynamic weighting. The paper presents such a new development and uses the multi-parameter design of a brushless pm motor to illustrate the approach.
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > EEE
|Date Deposited:||03 Jun 2001|
|Last Modified:||27 Mar 2014 19:57|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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