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This study aimed to investigate the accuracy of the artificial neural network in estimating thermal conductivity (k) of ferrofluid-based nanofluids. The parameters ofandhave been measured at 20–600.05, 0.1, and 0.2 vol.% and the results showed thatwas greater thanby 89%, which is obtained at 60and 0.2 vol.%. To estimatea three-layer ANN was developed that contained two, three, and one neurons, respectively. This neural network was able to estimatewith less than 0.8% error considering ofThe response surface methodology was also implemented, and it was observed that cubic polynomials, taking to account ofwill figure out the best results so thatcan be predicted with an error of less than 0.5%.

Using neural network and RSM to evaluate improvement in thermal conductivity of nanodiamond-iron oxide/antifreeze