Predictive modeling of bacterial growth in anaerobic biogas digester using artificial neural networks

Javad Jannatkhah , Haleh Karimmaslak , Asma Kisalaei


The main objective of this study is to determine the growth kinetics of mesophilic and thermophilic bacteria in biogas anaerobic digester using first order kinetic model, Monod kinetic model, diffusion model, Chen-Hashimoto model, Sing model and Cantois model. Nonlinear, stochastic models like artificial neural networks coupled with Monod kinetics was also applied for modeling the rate constants in anaerobic biogas digester. Thermophilic bacterial anaerobic digester is a found to be suitable for very hot weathers when compared with mesophilic bacterial anaerobic digester. Artificial neural network is proved to be an effective tool in predicting the rate equation when compared with other linear models.

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