Related Experiment Video
Updated: Aug 7, 2026

A Novel Bioreactor for High Density Cultivation of Diverse Microbial Communities
Published on: December 25, 2015
Neural networks as a tool for control and management of a biological reactor for treating hydrogen sulphide
A Elías1, G Ibarra-Berastegi, R Arias
1Department of Chemical and Environmental Engineering, Engineering Faculty, University of the Basque Country, Alda Urkijo s/n., 48013, Bilbao, Spain.
Abstract:
Based on an experimental database consisting of 194 daily cases, artificial neural networks were used to model the removal efficiency of a biofilter for treating hydrogen sulphide (H2S). In this work, the removal efficiency of the reactor was considered as a function of the changes in the air flow and concentration of H2S entering the biofilter. In order to obtain true representative values, the removal efficiencies (outputs) were measured 24 h after each input was changed. A MLP (multilayer perceptron 2-2-1) model with two input variables (unit flow and concentration of the contaminant fed into the biofilter) rendered good prediction values with a determination coefficient of 0.92 for the removal efficiency within the range studied. This means that the MLP model can explain 92% of the overall variability detected in the biofilter corresponding to a wide range of operating conditions.
More Related Videos
Related Concept Videos
Bioreactor Controls-I
Bioreactor Design and Operational System
Bioreactor Controls-II
Bioremediation
Microbial Wastewater Treatment
Bioreactor Controls-III

