To improve drinking water quality while reducing operating costs, many drin
king water utilities are investing in advanced process control and automati
on technologies. The use of artificial intelligence technologies, specifica
lly artificial neural networks, is increasing in the drinking water treatme
nt industry as they allow for the development of robust nonlinear models of
complex unit processes. This paper highlights the utility of artificial ne
ural networks in water quality modelling as well as drinking water treatmen
t process modelling and control through the presentation of several case st
udies at two large-scale water treatment plants in Edmonton, Alberta.