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Source identification of sudden water pollution events in the Dongliao River using a hybrid AI framework

https://doi.org/10.2139/ssrn.5465596
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Inverse transport problem of estimating point-like source using a Bayesian parametric method with MCMC
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Data-Driven Machine Learning in Environmental Pollution: Gains and Problems
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Support vector machines
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SWAT: Model Use, Calibration, and Validation
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On source identification method for sudden water pollution accidents
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Random Forest
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Data quality assessment in hydrological information systems
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Application of Nitrogen and Oxygen Isotopes for Source and Fate Identification of Nitrate Pollution in Surface Water: A Review
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Pollution Source Apportionment and Water Quality Risk Evaluation of a Drinking Water Reservoir during Flood Seasons
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Current Status of Emerging Contaminant Models and Their Applications Concerning the Aquatic Environment: A Review
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A first attempt to model global hydrology at hyper-resolution
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