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Minimal Function Calls Approach with On-Line Learning and Dynamic Weighting for Computationally Intensive Design Optimisation

Record type: Article

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.

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Citation

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 Default journal

More information

Published date: August 2000
Organisations: EEE

Identifiers

Local EPrints ID: 255902
URI: http://eprints.soton.ac.uk/id/eprint/255902
PURE UUID: 0535a308-e230-48fc-98bf-4e978fa409c5
ORCID for J.K. Sykulski: ORCID iD orcid.org/0000-0001-6392-126X

Catalogue record

Date deposited: 03 Jun 2001
Last modified: 18 Jul 2017 09:50

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Contributors

Author: J.K. Sykulski ORCID iD
Author: A.H. Al-Khoury
Author: K.F. Goddard

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