Modelling pathogen log10 reduction values achieved by activated sludge treatment using naïve and semi naïve Bayes network models

Water Research
Guido CarvajalStuart J Khan

Abstract

Risk management for wastewater treatment and reuse have led to growing interest in understanding and optimising pathogen reduction during biological treatment processes. However, modelling pathogen reduction is often limited by poor characterization of the relationships between variables and incomplete knowledge of removal mechanisms. The aim of this paper was to assess the applicability of Bayesian belief network models to represent associations between pathogen reduction, and operating conditions and monitoring parameters and predict AS performance. Naïve Bayes and semi-naïve Bayes networks were constructed from an activated sludge dataset including operating and monitoring parameters, and removal efficiencies for two pathogens (native Giardia lamblia and seeded Cryptosporidium parvum) and five native microbial indicators (F-RNA bacteriophage, Clostridium perfringens, Escherichia coli, coliforms and enterococci). First we defined the Bayesian network structures for the two pathogen log10 reduction values (LRVs) class nodes discretized into two states (< and ≥ 1 LRV) using two different learning algorithms. Eight metrics, such as Prediction Accuracy (PA) and Area Under the receiver operating Curve (AUC), provided a comparison ...Continue Reading

References

Jun 4, 2005·Applied and Environmental Microbiology·Valerie J HarwoodJoan B Rose
Jan 15, 2010·International Journal of Food Microbiology·J H SmidA H Havelaar
Oct 1, 2011·Artificial Intelligence in Medicine·M Julia FloresSteven Mascaro

❮ Previous
Next ❯

Related Concepts

Related Feeds

Bacteriophage: Phage Therapy

Phage therapy uses bacterial viruses (bacteriophages) to treat bacterial infections and is widely being recognized as an alternative to antibiotics. Here is the latest research.