LAUSR

ABSTRACT Asphaltene precipitation in petroleum industries is known as major problems. To solve problems there are approaches for inhibition of asphaltene precipitation, Asphaltene inhibitors are known effective and economical approach for inhibition and prevention of asphaltene precipitation. In the present study Adaptive neuro-fuzzy inference system (ANFIS) was coupled with Particle swarm optimization (PSO) to create a novel approach to predict effect of inhibitors on asphaltene precipitation as function of crude oil properties and concentration and structure of asphaltene inhibitors.in order to training and testing the algorithm, a total number of 75 experimental data was gathered from the literature. The results of this model showed that average absolute relative deviation (AARD), the coefficient of determination (R2) and root mean square error (RMSE) for the dataset of the algorithm are 2.5058, 0.99342 and 0.64238 respectively. According to the graphical and statistical reports, the proposed ANFIS-PSO has acceptable potential for investigation of effect on asphaltene inhibitors.