Artificial neural network prediction of CO emission and ash yield from co-combustion of empty fruit bunch, palm kernel shell and kaolin.

The quantity of ash yield and carbon monoxide (CO) emitted during co-combustion of empty fruit bunch (EFB), palm kernel shells (PKS) and kaolin in a grate furnace depend on the fuels mixing ratio, the combustion temperature and duration. These factors can be tuned to minimize ash deposition and CO emission which is partly responsible for the greenhouse effect. In this study, seventy-three (73) data points were obtained from combustion of EFB, PKS and kaolin mixtures based on D-optimal design.