LAUSR

Abstract In this paper, two types of machine learning, namely neuro-fuzzy inference system (ANFIS) and multilayer perceptron (MLP), have been studied to model light hydrocarbons’ solubility solvent in bitumen. The 268 number of experimental data is used in this work from different articles. The input parameters are Temperature (T), pressure (P), and molecular weight (MW) of hydrocarbons. The result shows the high performance of the MLP model with a two layers to predict the experimental values. The estimated values were investigated by statistical parameters such as R 2, MSE, and MARD%. According to, statistical parameters, the values of 0.99, 0.00081, and 0.68 for MLP, and 0.96, 0.0029, and 0.78 for ANFIS indicate the high performance of the MLP model. Comparison between established models and previous work indicates that the developed model can be a suitable technique for solubility modeling