AIMC Topic: Flocculation

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Predicting coagulation-flocculation process for turbidity removal from water using graphene oxide: a comparative study on ANN, SVR, ANFIS, and RSM models.

Environmental science and pollution research international
Three artificial intelligence (AI) data-driven techniques, including artificial neural network (ANN), support vector regression (SVR), and adaptive neuro-fuzzy inference system (ANFIS), were applied for modeling and predicting turbidity removal from ...

Predicting flocculant dosage in the drinking water treatment process using Elman neural network.

Environmental science and pollution research international
Predicting the flocculant dosage in the drinking water treatment process is essential for public health. However, due to the complexity of water quality and flocculation, many difficulties remain. The present study aimed to report on using artificial...

Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach.

Chemosphere
Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for its environmental disposal. To reduce the number of laboratory experiments, this study proposes a novel and hybrid machine learning (ML) method for the predi...

Prediction of coagulation and flocculation processes using ANN models and fuzzy regression.

Water science and technology : a journal of the International Association on Water Pollution Research
Coagulation and flocculation are two main processes used to integrate colloidal particles into larger particles and are two main stages of primary water treatment. Coagulation and flocculation processes are only needed when colloidal particles are a ...