Implementing artificial neural network models for real-time water colour forecasting in a water treatment plant1

Artificial neural network (ANN) technology has evolved from the experimental stage into actual industrial applications. To achieve this significant transition, careful planning and adjustment are required. This paper illustrates such an example in the water treatment industry. The project objective...

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Bibliographic Details
Published inJournal of environmental engineering and science Vol. 3; p. S15
Main Authors Zhang, Qing J, Cudrak, Audrey A, Shariff, Riyaz, Stanley, Stephen J
Format Journal Article
LanguageEnglish
Published Ottawa ICE Publishing 02.01.2004
Subjects
Forecasting
Neural networks
Raw water
Research projects
Water treatment
Water treatment plants
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Summary:Artificial neural network (ANN) technology has evolved from the experimental stage into actual industrial applications. To achieve this significant transition, careful planning and adjustment are required. This paper illustrates such an example in the water treatment industry. The project objective is to upgrade the ANN models from a previous research project and install the system on-line in the Rossdale Water Treatment Plant in Edmonton, Alberta, Canada, to forecast raw water colour one day ahead. The article discusses the important issues and techniques to upgrade the neural network model to the actual application. Furthermore, sufficient communication is also required between the designers and the users to address the applicability and user friendly issues in model implementation. Failure in communication can render the whole process ineffective. Possible improvements are also recommended for the future on-line applications. [PUBLICATION ABSTRACT] Key words: artificial neural network, river raw water, forecasting, water treatment.
ISSN:1496-2551
1496-256X