Computational intelligence and low cost sensors in biomass combustion process

Artificial intelligence techniques have been used for carbon monoxide and oxygen low cost sensors signal processing in biomass combustion. Considering a large scatter of the measured data two approximation tools using artificial neural networks have been tested for approximation of carbon monoxide emissions dependence on oxygen concentration in the flue gas: AForge. Neuro library and Neural Network Fitting Tool of Matlab. The comparable results of approximation have been obtained by testing of both approximation tools on the off-line measured data.