Using a supervised machine learning approach to predict water quality at the Gaza wastewater treatment plant
This paper presents the use of four machine learning algorithms including Gaussian process
regression (GPR), random forest (FR), extreme gradient boosting (XGB) and light gradient …
regression (GPR), random forest (FR), extreme gradient boosting (XGB) and light gradient …
Modelling the biological treatment process aeration efficiency: application of the artificial neural network algorithm
M Muloiwa, M Dinka… - Water Science & …, 2022 - iwaponline.com
The biological treatment process (BTP) is responsible for removing chemical oxygen
demand (COD) and ammonia using microorganisms present in wastewater. The BTP …
demand (COD) and ammonia using microorganisms present in wastewater. The BTP …
Application of Artificial Neural Network for predicting biomass growth during domestic wastewater treatment through a biological process
M Muloiwa, M Dinka… - Engineering in Life …, 2023 - Wiley Online Library
The biological treatment process is responsible for removing organic and inorganic matter in
wastewater. This process relies heavily on microorganisms to successfully remove organic …
wastewater. This process relies heavily on microorganisms to successfully remove organic …
Comparative Analysis of Machine Learning Algorithms for Forecasting Effluent Chemical Oxygen Demand in Wastewater Treatment Plants
S Gerami, A Akbarpour - Water Harvesting Research, 2024 - jwhr.birjand.ac.ir
Accurate prediction of wastewater effluent parameters is crucial for evaluating the
performance of wastewater treatment plants, as it significantly contributes to reducing time …
performance of wastewater treatment plants, as it significantly contributes to reducing time …