Prediction of bisphenol A contamination in Canadian municipal wastewater
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gp-bibliography.bib Revision:1.8010
- @Article{ZHOU:2022:jwpe,
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author = "Pengxiao Zhou and Zhong Li and Wael El-Dakhakhni and
Shirley Anne Smyth",
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title = "Prediction of bisphenol A contamination in Canadian
municipal wastewater",
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journal = "Journal of Water Process Engineering",
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volume = "50",
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pages = "103304",
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year = "2022",
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ISSN = "2214-7144",
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DOI = "doi:10.1016/j.jwpe.2022.103304",
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URL = "https://www.sciencedirect.com/science/article/pii/S2214714422007486",
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keywords = "genetic algorithms, genetic programming, Bisphenol A,
Contaminants of emerging concerns, Machine learning,
Theory of networks, wastewater treatment",
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abstract = "Bisphenol A (BPA) is one of the most common
contaminants of emerging concerns (CECs), which pose a
threat to human health. Conventional wastewater
treatment plants (WWTPs) are considered as the major
pathway of BPA entering the aqueous environment. To
control and mitigate BPA contamination in the aquatic
environment, predicting BPAs fate at WWTPs is critical.
In this study, three machine learning models, including
shared layer multi-task neural network (MLT-NN),
genetic programming (GP), and extra trees (ET) are used
to predict the effluent BPA concentration at twelve
municipal WWTPs across Canada. Additionally, the theory
of networks is adopted to analyze the interdependencies
among the influencing factors of BPA removal. It is
found that the proposed models can provide reasonable
BPA effluent concentration predictions. They have
advantages in alleviating data sparsity and imbalance,
improving model interpretability, and measuring
predictor importance, which is valuable for the
modeling of BPA and many other CECs. The network
analysis results imply there are moderate
interdependencies among various influencing factors of
BPA removal. Factors that significantly affect BPA
effluent concentration and are thus important for BPA
removal are identified. The results also show that BPA
is unlikely to be removed at primary treatment plants,
while BPA removal could be achieved through secondary
or tertiary treatment. This study presents an
integrated framework for the modeling and analysis of
BPA at WWTPs, which can provide direct and robust
decision support for the management of BPA as well as
other emerging contaminants in municipal wastewater",
- }
Genetic Programming entries for
Pengxiao Zhou
Zhong Li
Wael El-Dakhakhni
Shirley Anne Smyth
Citations