[HTML][HTML] The role of deep learning in urban water management: A critical review
Deep learning techniques and algorithms are emerging as a disruptive technology with the
potential to transform global economies, environments and societies. They have been …
potential to transform global economies, environments and societies. They have been …
A review on interpretable and explainable artificial intelligence in hydroclimatic applications
This review focuses on the use of Interpretable Artificial Intelligence (IAI) and eXplainable
Artificial Intelligence (XAI) models for data imputations and numerical or categorical …
Artificial Intelligence (XAI) models for data imputations and numerical or categorical …
Optimization of water quality index models using machine learning approaches
F Ding, W Zhang, S Cao, S Hao, L Chen, X Xie, W Li… - Water Research, 2023 - Elsevier
To optimize the water quality index (WQI) assessment model, this study upgraded the
parameter weight values and aggregation functions. We determined the combined weights …
parameter weight values and aggregation functions. We determined the combined weights …
Critical role of climate factors for groundwater potential mapping in arid regions: Insights from random forest, XGBoost, and LightGBM algorithms
Groundwater potential mapping (GPM) provides the valuable information on groundwater
volume that can be withdrawn from the aquifer without affecting the environmental …
volume that can be withdrawn from the aquifer without affecting the environmental …
Machine learning framework for intelligent aeration control in wastewater treatment plants: Automatic feature engineering based on variation sliding layer
Intelligent control of wastewater treatment plants (WWTPs) has the potential to reduce
energy consumption and greenhouse gas emissions significantly. Machine learning (ML) …
energy consumption and greenhouse gas emissions significantly. Machine learning (ML) …
Machine learning-assisted exploration for carbon neutrality potential of municipal sludge recycling via hydrothermal carbonization
In the context of advocating carbon neutrality, there are new requirements for sustainable
management of municipal sludge (MS). Hydrothermal carbonization (HTC) is a promising …
management of municipal sludge (MS). Hydrothermal carbonization (HTC) is a promising …
Spatiotemporal-aware machine learning approaches for dissolved oxygen prediction in coastal waters
Coastal waters face increasing threats from hypoxia, which can have severe consequences
for marine life and fisheries. This study aims to develop a machine learning approach for …
for marine life and fisheries. This study aims to develop a machine learning approach for …
Machine learning models for inverse design of the electrochemical oxidation process for water purification
Y Sun, Z Zhao, H Tong, B Sun, Y Liu… - … Science & Technology, 2023 - ACS Publications
In this study, a machine learning (ML) framework is developed toward target-oriented
inverse design of the electrochemical oxidation (EO) process for water purification. The …
inverse design of the electrochemical oxidation (EO) process for water purification. The …
Does institutional quality affect CO2 emissions? Evidence from explainable artificial intelligence models
Although the debate regarding the impact of high-quality institutional measures to address
climate change associated with global carbon dioxide (CO 2) emissions has gained …
climate change associated with global carbon dioxide (CO 2) emissions has gained …
Cascade ensemble learning for multi-level reliability evaluation
For complex systems involving multiple operating conditions and multiple failure modes, its
reliability analysis usually presents the cascade failure correlation between multiple levels …
reliability analysis usually presents the cascade failure correlation between multiple levels …