A Methodology for modeling Wastewater Treatment Process based on Uncertainty Theory

Wastewater treatment is a complicated dynamic process affected by microbial, chemical and physical factors. These variables are always uncertain. Due to the complex biological reaction mechanisms, the highly time-varying and multivariable aspects, the traditional analysis method in the description and simulation of complex reaction process and mechanism of wastewater treatment encountered challenges. However, we can use uncertainty theory to mine the rules behind the data and find the relationship between them. The Bayesian network is a powerful knowledge representation tool that deals explicitly with uncertainty. This paper employed the Bayesian network to make active exploration on the modeling of wastewater treatment system. An example is given to illustrate how to build a BN based sewage treatment system model.