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This research article presents a selection routine for the higher heating value prediction correlations based on the proximate composition data. Thirty-one correlations from two different types - proximate analysis-based correlations and ultimate analysis -based correlations - were computed and validated against the experimental data from two Chiang Rai regional crop residue biomasses, including cacao husk and corncob, as well as their torrefied biochar. The result showed that the correlation PC15 was the most accurate in our study with the mean absolute error MAE = 4.69%.
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