Evaluation of the linear and non-linear prediction models optimized with metaheuristics: Application to anaerobic digestion processes

Abstract

This research represents an evaluation study of the linear and non-linear mathematical methods applied to predict the biogas flow rate in anaerobic digestion processes. The anaerobic digestion model No.1 was used to generate the process data. For the prediction of the biogas flow rate the partially least squares regression, the locally weighted regression and the artificial neural networks were used. Two metaheuristic tools, here a genetic algorithm and an ant colony optimization algorithm were applied to improve the prediction models. They carried out the variable selection procedure. The implemented mathematical models could successfully perform the prediction of the biogas flow rate. Nevertheless, more robust and accurate prediction of the biogas flow rate was done with the help of the artificial neural networks. Here the error of prediction was about 9% while the coefficient of determination reached 0.97.