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Analysis used artificial neural networks to assess sediment quality at multiple stations, highlighting its efficacy.
Assessment of bottom sediment quality is vital in water resources management. The study collected sediment data at five monitoring stations in the Saigon River and its tributaries from 2013 to 2023. These monitoring data was used to construct our feedforward neutral network (FFNN) model. The model’s accuracy is 95.5% in assessing sediment quality. The study also presents a speedy method for evaluating the quality of bottom sediments in Vietnam.
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Nguyen et al. (2025) studied this question.
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