شماره ركورد كنفرانس :
4416
عنوان مقاله :
Prediction of the Amount of Sulfur Adsorption Using a GA-RBF Model
پديدآورندگان :
Mohebbi Armin Department of Chemical Engineering, Amirkabir University of Tech. (Tehran Polytechnic), Tehran, Iran , Ahmadi-pour Maryam Department of Gas Engineering, Petroleum University of Technology, Ahvaz, Iran , Mohebbi Milad Department of petroleum Engineering, Islamic Azad University, Fars Science and Research Branch, Shiraz, Iran
كليدواژه :
Sulfur adsorption , Model , GA , RBF , Prediction
عنوان كنفرانس :
دومين همايش ملي مهندسي و تكنولوژي هاي سبز براي آينده پايدار
چكيده فارسي :
This work highlights the application of one type of artificial neural network namely GA-RBF for prediction of sulfur adsorption in liquid phase of hydrocarbon solution of isotherm batch systems. The precision and reliability of developed model were studied by various graphical and statistical approaches. Initial sulfur concentration, utilized adsorbent weights, molecular weights and densities of solvent and solute, average size of adsorbent particle, Si/ Al ratio of adsorbent and temperature were used as input parameters of model and the model output was the amount of adsorption. Results show that the predictions of GA-RBF model is precise and reliable. The overall values of R2 and AARD% for GA-RBF model were 0.998 and 2.21 that show precision and robustness of the applied model
