Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil

In this paper, an artificial neural network (ANN) model was used to model and predict the desulfurization efficiency of AL-Ahdab crude oil (AHD). This study implements the artificial neural network (ANN) in modeling and predicting sulfur removal from AL-Ahdab crude oil for a better understanding and optimizing of the process operation. This study was based on data sets collected from previous work on AHD sour crude oil (3.9 wt% sulfur content). The developed model's accuracy was assessed by the mean squared error and goodness of fit (R2). In this study, fifteen neural network models for the desulfurization process were designed and validated. Results show that the developed model (9) is in excellent agreement with experimental data. Model (9) is the best model with the lowest mean square error (0.001), two hidden layers and 20 neurons and the value of the correlation coefficient (R2) is 0.999.