Several studies show that thermodynamic ionic liquid promoter, such as Tetra-n-butylammonium bro-mide (TBAB) can moderate the formation conditions of gas hydrates. In the current study, a SupportVector Machine (SVM) and coupling of SVM with Genetic Algorithm (GASVM) have been developed topredict semi-clathrate hydrate pressure of CO2, CH4, N2, H2, Ar, Xe and H2S in the presence of TBABionic liquid according to the critical temperature (Tc), critical pressure (Pc) and acentric factor (ω) ofabovementioned gases over wide ranges of temperature, pressure and concentration of TBAB. For imple-mentation of networks, 528 experimental data points collected from the published papers have beenemployed. Moreover, to verify both proposed models, regression analysis and statistical analysis such asmean square errors (MSEs), average relative deviations (ARDs), standard deviations (STDs) and root meansquare errors (RMSEs) have been conducted on the experimental and predicted values of semi-clathratehydrate pressure of gases in TBAB. While, the values of R2= 0.97759 and ARD = 0.25465132obtained forSVM model, coefficient of determination (R2) and Average Relative Deviation (ARD) of GASVM betweenthe experimental and predicted values are 0.99944 and 0.07180737 respectively. Finally, according tothe obtained results, in this contribution, ability and better performance of using GASVM as a correlationfor prediction of semi-clathrate hydrate pressure and temperature in TBAB has been shown against SVMmodel.
کلید واژگان :HydrateGasPressureSupport vector machineGenetic algorithm
ارزش ریالی : 600000 ریال
با پرداخت الکترونیک