DSpace
 

EMU I-REP >
09 School of Computing and Technology >
SCT – Journal Articles: Publisher & Author Versions (Post-Print Author Versions) – SCT >

Please use this identifier to cite or link to this item: http://hdl.handle.net/11129/2891

Title: Deploying An Artificial Neural Network Model for Solar Air Heating Modelling
Authors: Omojaro, Peter
Nwulu, Nnamdi
İlkan, Mustafa
School of Computing And Technology
TR214500
Keywords: Artificial Neural Network
Solar Air Heater
Renewable Energy
Modelling
Issue Date: 1-May-2013
Publisher: International Information Institute
Citation: Omojaro, P., Nwulu, N. I., & Ilkan, M. (2013). Deploying An Artificial Neural Network Model for Solar Air Heating Modelling. International Information Institute (Tokyo). Information, 16(5), 3249.
Abstract: Abstract In this work, the authors utilize Artificial Neural Networks to model the efficiency of solar air heaters. The underlying thermodynamic principles and factors affecting the performance of the solar air heater were considered and used for training and testing to determine the efficiency of the solar air heater. Using an input-output mapping approach, a back propagation learning algorithm based neural network was used to train and test measurable, controlled and conditional factors as input for the modeling architecture. The ...
Description: The file in this item is the publisher version (published version) of the article.
URI: http://hdl.handle.net/11129/2891
ISSN: 1343-4500
Appears in Collections:SCT – Journal Articles: Publisher & Author Versions (Post-Print Author Versions) – SCT

Files in This Item:

File Description SizeFormat
78.pdfPublisher Version1.39 MBAdobe PDFView/Open


This item is protected by original copyright

Recommend this item
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback