Incremental and stable training algorithm for wind turbine neural modeling
Keywords:
wind turbine, neural models, incremental algorithm, adaptive learning rateAbstract
Training and topology design of artificial neuralnetworks are important issues with largeapplication. This paper deals with an improvedalgorithm for feed forward neural networks (FNN) straining. The association of an incrementalapproach and the Lyapunov stability theoryaccomplishes both good generalization and stabletraining process. The algorithm is tested on windturbine modeling. Compared to the incrementalapproach and to the Lyapunov stability basedmethod, the association of both strategies givesinteresting results.Downloads
Published
2013-09-03
Issue
Section
Articles
License
Copyright 2022 by Faculty of Engineering University of Rijeka, Faculty of Civil Engineering University of Rijeka. All rights reserved. This material may not be reproduced or copied, in whole or in part, in any printed, mechanical, electronic, film, or other distribution and storage media without the written consent of the publisher.
The journal Engineering Review’s publishing procedure is performed in accordance with the publishing ethics statements, defined within the Publishing Ethics Resource Kit. The Ethics statement is available in the document Ethics Policies.