Harnessing the potential of microalgae-bacteria interaction for eco-friendly wastewater treatment: a review on new strategies involving machine learning and artificial …
In the pursuit of effective wastewater treatment and biomass generation, the symbiotic
relationship between microalgae and bacteria emerges as a promising avenue. This …
relationship between microalgae and bacteria emerges as a promising avenue. This …
Removal of pollutants from wastewater using coffee waste as adsorbent: A review
LL Kang, YN Zeng, YT Wang, JG Li, FP Wang… - Journal of Water …, 2022 - Elsevier
The problem of water pollution is becoming more and more serious, and many pollutants are
carcinogenic and pose a serious threat to global sustainable and green development …
carcinogenic and pose a serious threat to global sustainable and green development …
Uncertainty quantification of granular computing-neural network model for prediction of pollutant longitudinal dispersion coefficient in aquatic streams
Discharge of pollution loads into natural water systems remains a global challenge that
threatens water and food supply, as well as endangering ecosystem services. Natural …
threatens water and food supply, as well as endangering ecosystem services. Natural …
[HTML][HTML] Numerical modelling of hydraulic efficiency and pollution transport in waste stabilization ponds
This paper investigates the hydraulic performance and solute transport processes in waste
stabilization ponds (WSPs). A numerical model comprised of Reynolds-averaged Navier …
stabilization ponds (WSPs). A numerical model comprised of Reynolds-averaged Navier …
Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
F Bagherzadeh, AS Nouri, MJ Mehrani… - Process Safety and …, 2021 - Elsevier
Abstract Treatment of municipal wastewater to meet the stringent effluent quality standards is
an energy-intensive process and the main contributor to the costs of wastewater treatment …
an energy-intensive process and the main contributor to the costs of wastewater treatment …
Hybrid machine learning models for prediction of daily dissolved oxygen
Measuring water quality parameters is a significant step in many hydrological assessments.
Dissolved oxygen (DO) is one of these parameters that is an indicator of water quality …
Dissolved oxygen (DO) is one of these parameters that is an indicator of water quality …
Hybrid modelling of water resource recovery facilities: status and opportunities
Mathematical modelling is an indispensable tool to support water resource recovery facility
(WRRF) operators and engineers with the ambition of creating a truly circular economy and …
(WRRF) operators and engineers with the ambition of creating a truly circular economy and …
An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
B Szeląg, E Zaborowska, J Mąkinia - Journal of Water Process Engineering, 2023 - Elsevier
This study presents an advanced algorithm for selecting machine learning (ML) models for
nitrous oxide (N 2 O) emission prediction in wastewater treatment plants (WWTPs) …
nitrous oxide (N 2 O) emission prediction in wastewater treatment plants (WWTPs) …
Optimizing dissolved oxygen requirement and energy consumption in wastewater treatment plant aeration tanks using machine learning
AS Qambar, MM Al Khalidy - Journal of Water Process Engineering, 2022 - Elsevier
Most aeration tanks in wastewater treatment plants (WWTPs) operate at fixed dissolved
oxygen (DO) concentrations of 2.0 mg/L. Such control systems do not consider various …
oxygen (DO) concentrations of 2.0 mg/L. Such control systems do not consider various …
Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches
Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …