A Methodology for modeling Wastewater Treatment Process based on Uncertainty Theory

DOI

10.2991/iceep-17.2017.102How to use a DOI?

Keywords

Wastewater treatment system; Uncertainty theory ;Bayesian network; Modified sequencing batch reactor.

Abstract

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.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Dan Li
AU  - Tao Yuan
AU  - Xiao Feng Liang
PY  - 2017/06
DA  - 2017/06
TI  - A Methodology for modeling Wastewater Treatment Process based on Uncertainty Theory
BT  - Proceedings of the 2017 6th International Conference on Energy and Environmental Protection (ICEEP 2017)
PB  - Atlantis Press
SP  - 576
EP  - 582
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceep-17.2017.102
DO  - 10.2991/iceep-17.2017.102
ID  - Li2017/06
ER  -