Artificial neural network prediction of the biogas flow rate optimised with an ant colony algorithm

作者：Beltramo Tetyana^*; Ranzan Cassiano; Hinrichs Joerg; Hitzmann Bernd

来源：Biosystems Engineering, 2016, 143: 68-78.

DOI：10.1016/j.biosystemseng.2016.01.006

• Neural network
• Ant Colony Optimisation (ACO)
• Model-driven
• Modelling
• Biogas flow rate

The aim of this study was to develop a fast and robust methodology to analyse the biogas production process. The Anaerobic Digestion Model No.1 was used to simulate the co-digestion of agricultural substrates. Neural network models were used to predict the biogas flow rate. With the help of the ant colony optimfsation algorithm, the significant process variables were identified. Thus the model dimension was reduced and the model performance was improved. The achieved results showed that the approach gave a reliable way to analyse the biogas production process with respect to the significant process variables. This methodology could be further implemented to control the biogas production process and to manage the substrate composition.

• 出版日期2016-3