modeling of artificial neural network for predicting specific heat capacity of working fluid libr-h2o used in vapor absorption refrigeration system

Clicks: 297
ID: 217389
2011
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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 ANN’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.
Reference Key
singh2011internationalmodeling Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Dheerendra Vikram Singh;Govind Maheshwari
Journal International journal of offender therapy and comparative criminology
Year 2011
DOI
10.3991/ijoe.v7i2.1549
URL
http://online-journals.org/index.php/i-joe/article/view/1549
Keywords
artificial system network neural

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