A new approach for the prediction of the heat transfer rate of the wire-on-tube type heat exchanger––use of an artificial neural network model

This study presents an application of artificial neural networks (ANNs) to predict the heat transfer rate of the wire-on-tube type heat exchanger. A back propagation algorithm, the most common learning method for ANNs, is used in the training and testing of the network. To solve this algorithm, a co...

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Bibliographic Details
Published in:Applied thermal engineering 2003-02, Vol.23 (2), p.243-249
Main Author: Islamoglu, Yasar
Format: Article
Language:English
Subjects:
Applied sciences
Artificial neural network (ANN)
Devices using thermal energy
Energy
Energy. Thermal use of fuels
Exact sciences and technology
Heat exchanger
Heat exchangers (included heat transformers, condensers, cooling towers)
Heat transfer rate
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Summary:This study presents an application of artificial neural networks (ANNs) to predict the heat transfer rate of the wire-on-tube type heat exchanger. A back propagation algorithm, the most common learning method for ANNs, is used in the training and testing of the network. To solve this algorithm, a computer program was developed by using C++ programming language. The consistence between experimental and ANNs approach results was achieved by a mean absolute relative error
ISSN:1359-4311
DOI:10.1016/S1359-4311(02)00155-2