Forecasting water quality parameters using Random Forest and Gradient Boosting Machine regression models

Biochemical oxygen demand forecasting through ANN, ANFIS and SVM models

Mathematical modelling of the activated sludge process (ASP) enhances the understanding of the process and improves the quality of the effluent released. However, as the process is complex and nonlinear, mathematical modelling of the process has been a challenge. In this study, multi-layer perceptron artificial neural...

Daily River Suspended Sediment Load Forecasting Using Artificial Intelligence Models

Machine learning-based prediction of chlorophenol removal from wastewater using reverse osmosis

The results demonstrated that the Gradient Boosting algorithm can achieve the best performance in predicting chlorophenol removal, followed by the XGBoost algorithm, but neural networks performed the worst.

Hybrid machine learning–NSGA-II framework for multi-objective optimization of anaerobic digestion in wastewater treatment

Anaerobic digestion (AD) is a key process for sludge treatment, volume reduction, and energy recovery in wastewater treatment plants (WWTPs). Therefore, the use of artificial intelligence methods in ED is recommended for better sludge and wastewater management. With the development of artificial intelligence, this...

MACHINE LEARNING-BASED PREDICTION OF WATER QUALITY USING PHYSICOCHEMICAL AND ENVIRONMENTAL INDICATORS

The findings demonstrate that a parsimonious machine-learning framework can capture meaningful water-quality variability from multidimensional environmental measurements and provides a practical basis for identifying influential indicators and supporting targeted water-quality monitoring.

A comparative study of response surface methodology (RSM) and artificial neural networks (ANN) based optimization and modeling of paper mill effluent treatment using Lemna minor

Industrial effluents are a major source of water pollution, often leading to ecological imbalance and human health risks. Among these, paper mill effluent is particularly challenging to manage due to its high pollution load. This study aimed to evaluate the phytoremediation potential of Lemna minor for paper mill efflu...