Prediction of heavy metals adsorption by hydrochars and identification of critical factors using machine learning algorithms
F Zhao, L Tang, H Jiang, Y Mao, W Song… - Bioresource Technology, 2023 - Elsevier
Hydrochar has become a popular product for immobilizing heavy metals in water bodies.
However, the relationships between the preparation conditions, hydrochar properties …
However, the relationships between the preparation conditions, hydrochar properties …
A soft-sensor for sustainable operation of coagulation and flocculation units
Abstract Nowadays, Machine Learning (ML) techniques have become one of the most
widely used engineering tools due to their numerous advantages, including their continuous …
widely used engineering tools due to their numerous advantages, including their continuous …
Quantification of the antagonistic and synergistic effects of Pb2+, Cu2+, and Zn2+ bioaccumulation by living Bacillus subtilis biomass using XGBoost and SHAP
S Wang, Y Zhou, X You, B Wang, L Du - Journal of Hazardous Materials, 2023 - Elsevier
Bioaccumulation and adsorption are efficient methods for removing heavy metal ions (HMIs)
from aqueous environments. However, methods to quantifiably characterize the removal …
from aqueous environments. However, methods to quantifiably characterize the removal …
Simulation, prediction and optimization of typical heavy metals immobilization in swine manure composting by using machine learning models and genetic algorithm
H Guo, H Liu, S Wu - Journal of Environmental Management, 2022 - Elsevier
Abstract Machine learning (ML) is a novel method of data analysis with potential to
overcome limitations of traditional composting experiments. In this study, four ML models …
overcome limitations of traditional composting experiments. In this study, four ML models …
Heavy metals prediction in coastal marine sediments using hybridized machine learning models with metaheuristic optimization algorithm
This study proposes different standalone models viz: Elman neural network (ENN), Boosted
Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As …
Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As …
Machine learning for heavy metal removal from water: recent advances and challenges
Research on the removal of heavy metals (HMs) from contaminated waters, aiming at
ensuring the safety of water bodies, has shifted from direct experimental tests to machine …
ensuring the safety of water bodies, has shifted from direct experimental tests to machine …
Machine learning-based prediction of toxic metals concentration in an acid mine drainage environment, northern Tunisia
Abstract In northern Tunisia, Sidi Driss sulfide ore valorization had produced a large waste
amount. The long tailings exposure period and in situ minerals interactions produced an …
amount. The long tailings exposure period and in situ minerals interactions produced an …
Unraveling the role of Fe in As (III & V) removal by biochar via machine learning exploration
J Liu, Z Xu, W Zhang - Separation and Purification Technology, 2023 - Elsevier
Biochar adsorption is a conspicuous technology for As remediation, and Fe modification into
biochar is deemed an efficient approach to enhance As removal. Recently, immense …
biochar is deemed an efficient approach to enhance As removal. Recently, immense …
Machine learning framework for modeling flocculation kinetics using non-intrusive dynamic image analysis
The implementation of a machine learning (ML) model to improve both the effectiveness and
sustainability of the water treatment system is a significant challenge in the water sector, with …
sustainability of the water treatment system is a significant challenge in the water sector, with …
A review outlook on methods for removal of heavy metal ions from wastewater
SR Dhokpande, SM Deshmukh, A Khandekar… - Separation and …, 2024 - Elsevier
Severe environmental impacts of wastewater contamination include ecosystem deterioration
and health concerns to people. The significance of wastewater in the degradation of the …
and health concerns to people. The significance of wastewater in the degradation of the …