The potential of new ensemble machine learning models for effluent quality parameters prediction and related uncertainty
A Sharafati, SBHS Asadollah… - Process Safety and …, 2020 - Elsevier
Accurate simulation of wastewater effluent parameters is a vital concern to reduce the
operational costs of a wastewater treatment plant. In this way, a reliable predictive model is a …
operational costs of a wastewater treatment plant. In this way, a reliable predictive model is a …
Prediction of water quality indexes with ensemble learners: Bagging and Boosting
One of the most crucial jobs to improve water resources management plans is the
assessment of river water quality. A water quality index (WQI) takes multiple water quality …
assessment of river water quality. A water quality index (WQI) takes multiple water quality …
Machine learning algorithms for the forecasting of wastewater quality indicators
Stormwater runoff is often contaminated by human activities. Stormwater discharge into
water bodies significantly contributes to environmental pollution. The choice of suitable …
water bodies significantly contributes to environmental pollution. The choice of suitable …
Artificial intelligence based ensemble modeling of wastewater treatment plant using jittered data
In this study, black box artificial intelligence models (AI) including feed forward neural
network (FFNN), support vector regression (SVR) and adaptive neuro-fuzzy inference …
network (FFNN), support vector regression (SVR) and adaptive neuro-fuzzy inference …
Wastewater treatment plant performance analysis using artificial intelligence–an ensemble approach
In the present study, three different artificial intelligence based non-linear models, ie feed
forward neural network (FFNN), adaptive neuro fuzzy inference system (ANFIS), support …
forward neural network (FFNN), adaptive neuro fuzzy inference system (ANFIS), support …
[HTML][HTML] Predicting quality parameters of wastewater treatment plants using artificial intelligence techniques
Estimating wastewater treatment plants'(WWTPs) influent parameters such as 5-day
biological oxygen demand (BOD 5) and chemical oxygen demand (COD) is vital for …
biological oxygen demand (BOD 5) and chemical oxygen demand (COD) is vital for …
Predicting wastewater treatment plant quality parameters using a novel hybrid linear-nonlinear methodology
Biochemical oxygen demand (BOD), chemical oxygen demand (COD), total dissolved solids
(TDS) and total suspended solids (TSS) are the most commonly regulated wastewater …
(TDS) and total suspended solids (TSS) are the most commonly regulated wastewater …
River water quality index prediction and uncertainty analysis: A comparative study of machine learning models
SBHS Asadollah, A Sharafati, D Motta… - Journal of environmental …, 2021 - Elsevier
Abstract The Water Quality Index (WQI) is the most common indicator to characterize surface
water quality. This study introduces a new ensemble machine learning model called Extra …
water quality. This study introduces a new ensemble machine learning model called Extra …
Model construction and application for effluent prediction in wastewater treatment plant: Data processing method optimization and process parameters integration
R Wang, Y Yu, Y Chen, Z Pan, X Li, Z Tan… - Journal of Environmental …, 2022 - Elsevier
Wastewater treatment based on the activated sludge process is complex process, which is
easily affected by influent quality, aeration time and other factors, leading to unstable …
easily affected by influent quality, aeration time and other factors, leading to unstable …
[PDF][PDF] Predictive performance modeling of Habesha brewery wastewater treatment plant using artificial neural networks
EB Hassen, AM Asmare - Chem. Int, 2019 - academia.edu
The aim of wastewater treatment process is to achieve a treated effluent and sludge quality
that is environmentally safe for disposal and/or reuse (Fezzi, 2015). Considering the …
that is environmentally safe for disposal and/or reuse (Fezzi, 2015). Considering the …