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[HTML][HTML] Applications of machine learning to water resources management: A review of present status and future opportunities
Water is the most valuable natural resource on earth that plays a critical role in the socio-
economic development of humans worldwide. Water is used for various purposes, including …
economic development of humans worldwide. Water is used for various purposes, including …
Applications of deep learning in water quality management: A state-of-the-art review
Excellent water quality (WQ) is an indispensable element in ensuring sustainable water
resource development. It is highly associated with the 3rd (good health and well-being), the …
resource development. It is highly associated with the 3rd (good health and well-being), the …
Predicting lake water quality index with sensitivity-uncertainty analysis using deep learning algorithms
Regular monitoring and assessment of water quality is essential to maintain the quality of
lake water. A commonly used method for assessing water quality is the Water Quality Index …
lake water. A commonly used method for assessing water quality is the Water Quality Index …
Exploring potential machine learning application based on big data for prediction of wastewater quality from different full-scale wastewater treatment plants
Water pollution generated from intensive anthropogenic activities has emerged as a critical
issue concerning ecosystem balance and livelihoods worldwide. Although optimizing …
issue concerning ecosystem balance and livelihoods worldwide. Although optimizing …
Current status and prospects of algal bloom early warning technologies: A Review
Y Peng, W Zhang, X Yang, Z Zhang, G Zhu… - Journal of Environmental …, 2024 - Elsevier
In recent years, frequent occurrences of algal blooms due to environmental changes have
posed significant threats to the environment and human health. This paper analyzes the …
posed significant threats to the environment and human health. This paper analyzes the …
Short-term Lake Erie algal bloom prediction by classification and regression models
The recent outbreaks of harmful algal blooms in the western Lake Erie Basin (WLEB) have
drawn tremendous attention to bloom prediction for better control and management. Many …
drawn tremendous attention to bloom prediction for better control and management. Many …
A secondary modal decomposition ensemble deep learning model for groundwater level prediction using multi-data
X Cui, Z Wang, N Xu, J Wu, Z Yao - Environmental Modelling & Software, 2024 - Elsevier
Groundwater level (GWL) prediction is important for ecological protection and resource
utilization; it helps in formulating policies for artificial groundwater recharge, modifying the …
utilization; it helps in formulating policies for artificial groundwater recharge, modifying the …
A deep learning method for cyanobacterial harmful algae blooms prediction in Taihu Lake, China
Abstract Cyanobacterial Harmful Algae Blooms (CyanoHABs) in the eutrophic lakes have
become a global environmental and ecological problem. In this study, a CNN-LSTM …
become a global environmental and ecological problem. In this study, a CNN-LSTM …
Assessment and a review of research on surface water quality modeling
J Bai, J Zhao, Z Zhang, Z Tian - Ecological Modelling, 2022 - Elsevier
Numerical simulation is an effective way to study the transport and transformation of
pollutants in surface water bodies. Widely used models include AQUATOX, CE-QUAL-W2 …
pollutants in surface water bodies. Widely used models include AQUATOX, CE-QUAL-W2 …
[HTML][HTML] Time-series modelling of harmful cyanobacteria blooms by convolutional neural networks and wavelet generated time-frequency images of environmental …
Early warning systems for harmful cyanobacterial blooms (HCBs) that enable precautional
control measures within water bodies and in water works are largely based on inferential …
control measures within water bodies and in water works are largely based on inferential …