Share

IIR document

Prediction of the heat transfer rate of a single layer wire-on-tube type heat exchanger using ANFIS.

Author(s) : HAYATI M., REZAEI A., SEIFI M.

Type of article: Article, IJR article

Summary

In this paper, the authors apply 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 back propagation 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, they 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 modelling heat exchangers for heat transfer analysis.

Available documents

Format PDF

Pages: pp. 1914-1917

Available

  • Public price

    20 €

  • Member price*

    Free

* Best rate depending on membership category (see the detailed benefits of individual and corporate memberships).

Details

  • Original title: Prediction of the heat transfer rate of a single layer wire-on-tube type heat exchanger using ANFIS.
  • Record ID : 2009-2276
  • Languages: English
  • Source: International Journal of Refrigeration - Revue Internationale du Froid - vol. 32 - n. 8
  • Publication date: 2009/12

Links


See other articles in this issue (8)
See the source

Indexing