Neural Network Comparing the Performances of the Training Functions for Predicting the Value of Specific Heat of Refrigerant in Vapor Absorption Refrigeration System
Year: 2011
Type: article
Abstract: The objective of this work is to compare performances of three training functions (TRAINBR, TRAINCGB and TRAINCGF) used for training neural network for predicting the value of the specific heat capacity of working fluid, LiBr-H 2 O, used in vapour absorption refrigeration system.The comparison is shown on the basis of percentage relative error, coefficient of multiple determination R-square, root mean square error and sum of the square due to error.
DOI: 10.5120/2276-2944
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2139043862