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Improving groundwater vulnerability assessment using machine learning
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DOI：10.1016/j.jes.2024.12.024.png)
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Abstract
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Keywords:
Machine learning
Water quality
Environmental impact
Convolutional neural network
Artificial intelligence
Arsenic
Fluoride
Nitrate
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