UPM Institutional Repository

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 (2014) Development of artificial neural network model in predicting performance of the smart wind turbine blade. Journal of Mechanical Engineering and Sciences, 6. pp. 734-745. ISSN 2289-4659; ESSN: 2231-8380

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.


Download File

[img]
Preview
PDF (Abstract)
Development of artificial neural network model in predicting performance of the smart wind turbine blade.pdf

Download (83kB) | Preview

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Publisher: Universiti Malaysia Pahang Publisher
Keywords: Artificial neural network; Back-propagation; Multiple back-propagation; Non-linear autoregressive exogenous model
Depositing User: Nabilah Mustapa
Date Deposited: 20 Jun 2015 06:49
Last Modified: 17 Apr 2017 09:26
URI: http://psasir.upm.edu.my/id/eprint/37062
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item