Recently, Predicting the membrane processes performance with the usage of experimental models let the users to optimize the processes operating conditions. In this research, Artificial Neural Network (ANN) model for Ultrafiltration processes were evaluated by using oil-water separation experimental data. The comparison between the results from the mentioned model and experimental data showed that the neural network model can well predict experimental results. The Multi Layers Perceptron (MLP) neural network feed forward along with Propagation learning algorithm and Levenberg-Marquardt function with 2 inputs and outputs were implemented. Tansig activation algorithm was used for the hidden layer and Purelin algorithm was utilized for the output layer. Furthermore, 5 neurons were defined for the hidden layer. After processing the data, 70 percent were allocated for learning, 15% were allocated for validity, and the remaining 15% were allocated for the experience. The achieved results with the aforementioned method had a suitable accuracy.
