ANN-Kriging hybrid model for predicting carbon and inorganic phosphorus recovery in hydrothermal carbonization.

Modeling of hydrothermal carbonization (HTC) of poultry litter to high-value materials was conducted in order to understand the process and predict the influence of process parameters on product properties. Reaction temperature and time were considered as inputs, whereas carbon and inorganic phosphorous recovery were considered as responses in the model. Artificial neural network (ANN) model was used in order to correlate the process parameters to the outputs.