Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/43791
Title: | Development of artificial neural network model in predicting performance of the smart wind turbine blade | Authors: | Supeni, EE Epaarachchi, JA Islam, MM Lau, KT |
Issue Date: | 2014 | Source: | Journal of mechanical engineering and sciences, 2014, v. 6, p. 734-745 | Abstract: | This paper demonstrates the applicability of artificial neural networks (ANNs) that use multiple bck-propagation networks (MBP) and a non-linear autoregressive exogenous model (NARX) for predicting the deflection of a smart wind turbine blade specimen. A neural network model has been developed to perform the deflection with respect to the number of wires required as the output parameter, and parameters such as load, current, time taken and deflection as the input parameters. The network has been trained with experimental data obtained from experimental work. The various stages involved in the development of a genetic algorithm based neural network model are addressed in detail in this paper. | Keywords: | Artificial neural network Back-propagation Multiple back-propagation Non-linear autoregressive exogenous model |
Publisher: | Universiti Malaysia Pahang | Journal: | Journal of mechanical engineering and sciences | ISSN: | 2289-4659 | DOI: | 10.15282/jmes.6.2014.1.0071 | Rights: | © Universiti Malaysia Pahang, Malaysia The Journal of Mechanical Engineering & Sciences is an open access journal. All open access papers are licensed and distributed under the terms of the Creative Commons Attribution- Non-Commercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/), which permits authors and readers unrestricted use, distribution, and reproduction the material in any medium, provided that the original work is properly cited. This is enabled under the terms of Attribution and Non-Commercial usage of the material. The following publication Supeni, E. E., Epaarachchi, J. A., Islam, M. M., & Lau, K. T. (2014). Development of artificial neural network model in predicting performance of the smart wind turbine blade. Journal of mechanical engineering and sciences, 2014, v. 6, p. 734-745 is available at https://doi.org/10.15282/jmes.6.2014.1.0071 |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Supeni_Development_Artificial_Neural.pdf | 514.28 kB | Adobe PDF | View/Open |
Page views
105
Last Week
0
0
Last month
Citations as of Apr 21, 2024
Downloads
45
Citations as of Apr 21, 2024
SCOPUSTM
Citations
11
Last Week
0
0
Last month
Citations as of Apr 19, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.