Journal
INTERNATIONAL JOURNAL OF REFRIGERATION-REVUE INTERNATIONALE DU FROID
Volume 32, Issue 8, Pages 1914-1917Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ijrefrig.2009.05.012
Keywords
Heat exchanger; Finned tube; Modelling; Heat transfer; Neural network; Fuzzy logic
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In this paper, we applied an Adaptive Neuro-Fuzzy Inference System (ANFIS) model for prediction of the heat transfer rate of the wire-on-tube type heat exchanger. Limited experimental data was used for training and testing ANFIS configuration with the help of hybrid learning algorithm consisting of backpropagation and least-squares estimation. The predicted values are found to be in good agreement with the actual values from the experiments with mean relative error less than 2.55%. Also, we compared the proposed ANFIS model to an ANN approach. Results show that the ANFIS model has more accuracy in comparison to ANN approach. Therefore, we can use ANFIS model to predict the performances of thermal systems in engineering applications, such as modeling heat exchangers for heat transfer analysis. (C) 2009 Elsevier Ltd and IIR. All rights reserved.
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