Development of artificial neural network model in predicting performance of the smart wind turbine blade

Citation

Supeni, Eris Elianddy and Epaarachchi, Jayantha Ananda and Islam, Md Mainul and Lau, Kin Tak (2013) Development of artificial neural network model in predicting performance of the smart wind turbine blade. In: 3rd Malaysian Postgraduate Conference (MPC2013), 4-5 July 2013, Education Malaysia Australia (EMA), Sydney, New South Wales, Australia. (pp. 233-242).

Abstract

This paper demonstrates the applicability of Artificial Neural Networks (ANNs) that use Multiple Back-Propagation networks (MBP) and Non-linear Autoregressive with Exogenous (NARX) for predicting the deflection of the smart wind turbine blade specimen. A neural network model has been developed to perform the deflection with respect to a number of wires required as the output parameter. The parameter includes load, current, time taken and deflection as input parameters. The network has been trained with experimental data obtained from experimental work. The various stages involved in the development of genetic algorithm based neural network model are addressed at length in this paper.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
Keywords:	Artificial neural network; Back-propagation; Multiple back-propagation; Non-linear autoregressive with exogenous
Depositing User:	Nabilah Mustapa
Date Deposited:	03 Sep 2018 04:54
Last Modified:	03 Sep 2018 04:54
URI:	http://psasir.upm.edu.my/id/eprint/65086
Statistic Details:	View Download Statistic

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