Optimization of Enhanced Coagulation in Water Treatment using Bayesian Networks
Abstract
As a result of the potential health effects of disinfection byproducts, there is extensive interest in alternative treatment technologies which lessen their formation. The potential for enhanced coagulation to improve the removal efficiency of organic matter and thus decrease the formation of disinfection byproducts is identified. A Bayesian Network model is used to simulate different coagulation conditions for purposes of determining optimal conditions for enhanced coagulation. The causal dependence relationships amongst the variables (e.g. coagulant, pH, temperature, etc.) are encoded in a Bayesian network structure to identify the most advantageous configuration of treatment options.
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