Wei, H. orcid.org/0000-0002-4704-7346 (2019) Boosting wavelet neural networks using evolutionary algorithms for short-term wind speed time series forecasting. In: Rojas, I., Joya, G. and Catala, A., (eds.) Proceedings of the 2019 International Work-Conference on Artificial Neural Networks (Advances in Computational Intelligence). 2019 International Work-Conference on Artificial Neural Networks (Advances in Computational Intelligence), 12-14 Jun 2019, Gran Canaria, Spain. Lecture Notes in Computer Science (11506). Springer , pp. 15-26. ISBN 9783030205201
Abstract
This paper addresses nonlinear time series modelling and prediction problem using a type of wavelet neural networks. The basic building block of the neural network models is a ridge type function. The training of such a network is a nonlinear optimization problem. Evolutionary algorithms (EAs), including genetic algorithm (GA) and particle swarm optimization (PSO), together with a new gradient-free algorithm (called coordinate dictionary search optimization – CDSO), are used to train network models. An example for real speed wind data modelling and prediction is provided to show the performance of the proposed networks trained by these three optimization algorithms.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: | |
Editors: |
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Copyright, Publisher and Additional Information: | © 2019 Springer. This is an author-produced version of a paper subsequently published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Neural network; Wavelet; Boosting; Optimization; Evolutionary algorithms; Time series; Wind speed; Forecasting; Data-Driven modelling |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 May 2019 14:13 |
Last Modified: | 16 May 2020 00:38 |
Status: | Published |
Publisher: | Springer |
Series Name: | Lecture Notes in Computer Science |
Refereed: | Yes |
Identification Number: | 10.1007/978-3-030-20521-8_2 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:146277 |