Modeling of Artificial Neural Network for Predicting Specific Heat capacity of working fluid LiBr-H2O used in Vapor Absorption Refrigeration System

Authors

  • Dheerendra Vikram Singh Shri Vaishnav Institute of Technology and Science
  • Govind Maheshwari Institute of Engineering and technology-DAVV

DOI:

https://doi.org/10.3991/ijoe.v7i2.1549

Keywords:

Artificial neural network, Refrigeration system, LiBr-H2O

Abstract


The objective of this work is to model an artificial neural network (ANN) to predict the value of specific heat capacity of working fluid LiBr-H2O used in vapour absorption refrigeration systems. A feed forward back propagation algorithm is used for the network, which is most popular for ANN. The consistence between experimental and ANNâ??s approach result was achieved by a mean relative error -0.00573, sum of the squares due to error0.00321, coefficient of multiple determination R-square 0.99961and root mean square error 0.01573 for test data. These results had been achieved in Matlab environment and the use of derived equations in any programmable language for deriving the specific heat capacity of LiBr-H2O solution.

Author Biography

Dheerendra Vikram Singh, Shri Vaishnav Institute of Technology and Science

Assistant Professor in Mechanical Engineering Department.

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Published

2011-05-06

How to Cite

Singh, D. V., & Maheshwari, G. (2011). Modeling of Artificial Neural Network for Predicting Specific Heat capacity of working fluid LiBr-H2O used in Vapor Absorption Refrigeration System. International Journal of Online and Biomedical Engineering (iJOE), 7(2), pp. 54–56. https://doi.org/10.3991/ijoe.v7i2.1549

Issue

Vol. 7 No. 2 (2011)

Section

Short Papers

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