In this study, adsorption data for the case of energetically heterogeneous solid surface
are modeled using artificial neural network. A neural network with three hidden
neurons, including the bias, was able to predict very accurately the temperature
dependency of adsorption data. The results were compared with experimental data
(over temperature range 273-313 K and 0-2 MPa pressure) and it was found that the
predictions of the artificial neural network model fit the experimental data very
accurately.