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Prediction of Water Demands in a Water Treatment Plant Using an Artificial Neural Network Model

Zoe Jingyu Zhu, W. Guo, B. MacKay and Edward McBean (2011)
University of Guelph
DOI: https://doi.org/10.14796/JWMM.R241-16
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Abstract

To provide improvements in efficiency and the ability to respond to changing external conditions, an artificial neural network (ANN) model is used to characterize the contents of reservoir(s) and water tower(s) sufficient to meet water demands. Maintaining water levels and daily treatment quantities can be effective to reduce the formation of disinfection byproducts (DBPs). Predictive models are developed to investigate the effects of maximum daily temperatures, incoming solar radiation and total daily precipitation (which influences water demands) and DBP formation at the water treatment plant.

ANNs are semi-parametric regression estimators, and are well suited for predicting water demands and water quality as they can approximate virtually any function, to varying degrees of accuracy. In this application, predictions of water demand and DBPs are obtained using a simple back-propagation neural network. A comparative evaluation of the stepwise regression method and the ANN model are provided. The results show that the ANN obtains better accuracy than the regression method: it produced R2 = 0.84 as compared to R2 = 0.71 obtained by standard regression.

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PAPER INFO

Identification

CHI ref #: R241-16 749
Volume: 19
DOI: https://doi.org/10.14796/JWMM.R241-16
Cite as: CHI JWMM 2011;R241-16

Publication History

Received: N/A
First decision: N/A
Accepted: N/A
Published: February 15, 2011

Status

# reviewers: 2
Version: Final published

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© 2011 CHI. Some rights reserved.

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Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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All papers published in the JWMM are licensed under a Creative Commons Attribution 4.0 International License (CC BY).

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AUTHORS

Zoe Jingyu Zhu

University of Guelph, Guelph, ON, Canada
ORCiD:

W. Guo

University of Guelph, Guelph, ON, Canada
ORCiD:

B. MacKay

University of Guelph, Guelph, ON, Canada
ORCiD:

Edward McBean

University of Guelph, Guelph, ON, Canada
ORCiD:


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  JWMM content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0 DEED)


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