Hybrid neural modelling of anaerobic wastewater treatment processes
(2001) Water Science and Technology — Vol. 43, n° 1, p. 43-50 (2001)
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- Abstract
- (en) This paper presents a hybrid approach for the modelling of an anaerobic digestion process. The hybrid model combines a feed-forward network, describing the bacterial kinetics, and the a priori knowledge based on the mass balances of the process components. We have considered an architecture which incorporates the neural network as a static model of unmeasured process parameters (kinetic growth rate) and an integrator for the dynamic representation of the process using a set of dynamic differential equations. The paper contains a description of the neural network component training procedure. The performance of this approach is illustrated with experimental data.
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Citations
Karama, A., Bernard, O., Genovesi, A., Dochain, D., Benhammou, A., & Steyer, J.-P. (2001). Hybrid neural modelling of anaerobic wastewater treatment processes. Water Science and Technology, 43(1), 43-50. https://hdl.handle.net/2078.5/58683 (Original work published 2001)