In the present study, using modelling based on experimental data, models for predicting the hydrogen adsorption isotherm were presented. The three Automatic Learning of Algebraic Models (ALAMO), feed-forward artificial neural networks (ANNs), and group method of data handling-type polynomial neural networks (GMDH-PNN) were constructed. The created models were evaluated to predict the equilibrium data of hydrogen storage on carbon nanostructures, including activated carbons doped with palladium (Pd) nanoparticles, fullerene pillared graphene nanocomposites, and nickel (Ni)-decorated carbon nanotubes. The inputs were nanostructure characteristics such as surface area, porevolume, and thermodynamic conditions such as pressure. The generalization of the trained models was acceptable, and the models successfully predicted the hydrogen adsorption isotherm for new inputs. The relative error percentage for most data points is less than 4%, which demonstrates their applicability in determining adsorption isotherms for any operating conditions. By performing error analysis calculations, it was shown that the ALAMO model has the highest accuracy. Also, sensitivity analysis calculations show that pressure is the most influential parameter in the adsorption process. Besides, by performing Genetic Algorithm (GA) optimization using the ALAMO model, the amount of pressure and adsorbent properties were determined so that the amount of hydrogen adsorption is maximized. According to the optimization results based on the GA, the higher the pressure, the greater the amount of hydrogen adsorption. The nanotubes with a surface area of 194.15 m2/g, a total volume of 1.8 cm3/g, micropore volume of 0.097 cm3/g, and mesopore volume of 0.963 cm3/g, graphene with a surface area of 2977.13 m2/g, a total volume of 1.5134 cm3/g, density of 617.45 kg/m3 , and activated carbon at pressures less than 30 bar with a surface of 2546.36 m2/g, a total volume of 1.237 cm3/g, micropore volume of 0.839 cm3 /g, and activated carbon at pressures more than 30 bar with a surface of 3027 m2/g, a total volume of 1.343 cm3/g, a micropore volume of 0.9582 cm3 /g, and a mesopore volume of 1.23 cm3/g, have the highest amount of stored hydrogen.

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