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This paper presents a computer-based first law and exergy analysis applied to vapour compression refrigeration systems for determining subcooling and superheating effects of environmentally safe new refrigerants. Three refrigerants are considered: R134a, R407c and R410a. It is found that subcooling and superheating temperatures directly influence the system performance as both condenser and evaporator temperatures are affected. The thermodynamic properties of the refrigerants are formulated using artificial neural network (ANN) methodology. Six ANNs were trained to predict various properties of the three refrigerants. The training and validation of the ANNs were performed with good accuracy. The correlation coefficient obtained when unknown data were used to the networks were found to be equal or very near to 1 which is very satisfactory. Additionally, the present methodology proved to be much better than the linear multiple regression analysis. From the analysis of the results it is found that condenser and evaporator temperatures have strong effects on coefficient of performance (COP) and system irreversibility. Also both subcooling and superheating affect the system performance. This effect is similar for R134a and R407c, and different for R410a. [ABSTRACT FROM AUTHOR]