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Modeling of Microplastic Contamination Using Soft Computational Methods: Advances, Challenges, and Opportunities

Emerging contaminants and associated treatment technologies 2024 7 citations

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Researchers reviewed the application of soft computational methods — including machine learning and statistical modeling — to predict and map microplastic contamination, identifying advances in model accuracy alongside persistent challenges around data scarcity and environmental variability.

Microplastic (MP) pollution has become a global concern due to its impact on ecosystems, wildlife, and potentially human health. Inferential and predictive modelling of this phenomenon using soft computational methods adds a valuable dimension to its research. This...

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