Neural Network Comparing the Performances of the Training Functions for Predicting the Value of Specific Heat of Refrigerant in Vapor Absorption Refrigeration System | Zendy

Dheerendra Vikram Singh | Zendy; Govind Maheshwari | Zendy; Ritu Shrivastav | Zendy; Durgesh Kumar Mishra | Zendy

Open Access

Neural Network Comparing the Performances of the Training Functions for Predicting the Value of Specific Heat of Refrigerant in Vapor Absorption Refrigeration System

Author(s) -

Dheerendra Vikram Singh,

Govind Maheshwari,

Ritu Shrivastav,

Durgesh Kumar Mishra

Publication year - 2011

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/2276-2944

Subject(s) - refrigerant , computer science , refrigeration , artificial neural network , value (mathematics) , training (meteorology) , absorption refrigerator , process engineering , thermodynamics , artificial intelligence , machine learning , meteorology , heat exchanger , physics , engineering

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, LiBrH2O, 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.

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