Dataset of experimental and adaptive neuro-fuzzy inference system (ANFIS) model prediction of R600a/MWCNT nanolubricant in a vapour compression system

T. O. Babarinde, S. A. Akinlabi, and D. M. Madyira, “Investigation of vapour compression refrigeration system using R600a with graphene Nano lubricant achived for every mass charge of R600a with graphene natural refrigerants have been adopted as substitute for HFC refrigerants in VCRS and R600a is one of the,” vol. 063104, p. 63104, 2012. F. M. Ekundayo and T. O. Babarinde, “Performance investigation of TiO2 nano fluid based lubricant on exergy of VCRS working with a mixture Of R290/R600,” vol. 8, no. 10, pp. 2672–2678, 2019. E. W. Lemmon, M. L. Huber, and M. O. Mclinden, “NIST reference fluid thermodynamic and transport properties — REFPROP.” Madyira, 2019, Investigation of household refrigerator system with varied capillary tube length investigation of household refrigerator system with varied capillary tube length, J. Phys.: Conf. Ser., 1378 Adedeji, 2020, Wind turbine power output very short-term forecast : a comparative study of data clustering techniques in a PSO-ANFIS model, J. Clean. Prod., 254, 1, 10.1016/j.jclepro.2020.120135