Estimation of higher heating value of coal based on proximate analysis using support vector regression

To estimate the higher heating value (HHV) of coals based on proximate analysis, a nonlinear model termed support vector regression (SVR) is introduced in this work. A total of 167 Chinese coal samples and 4540 U.S. coal samples were employed to develop and verify the SVR-based correlations. The estimation results indicated that the average absolute errors from estimating the HHV of Chinese and U.S. coals were only 2.16% and 2.42%, respectively. Some published correlations were also employed and redeveloped with the Chinese and U.S. coals to obtain a comparison with the SVR-based correlations developed in the present work. The results indicate that the SVR-based correlations can be more accurate than the published correlations. Attempts were also made to develop a universal correlation for coals from different regions. The simulation results indicate that the correlation between the proximate analysis and HHV of coals from different geographical regions is varied. For coals from different regions, developing and using different correlations can obtain much higher accuracy in estimating the HHV from proximate analysis.