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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Description/Abstract
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.
| Item Type: | Article |
|---|---|
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > EEE |
| Item ID: | 255902 |
| Date Deposited: | 03 Jun 2001 |
| Last Modified: | 02 Mar 2012 11:57 |
| Contributors: | Sykulski, J.K. (Author) Al-Khoury, A.H. (Author) Goddard, K.F. (Author) |
| Date: | August 2000 |
| Status: | Published |
| Further Information: | Google Scholar |
| URI: | http://eprints.soton.ac.uk/id/eprint/255902 |
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