IoT-enabled water distribution systems—A comparative technological review
Water distribution systems are one of the critical infrastructures and major assets of the water
utility in a nation. The infrastructure of the distribution systems consists of resources …
utility in a nation. The infrastructure of the distribution systems consists of resources …
[HTML][HTML] Water quality prediction and classification based on principal component regression and gradient boosting classifier approach
Estimating water quality has been one of the significant challenges faced by the world in
recent decades. This paper presents a water quality prediction model utilizing the principal …
recent decades. This paper presents a water quality prediction model utilizing the principal …
Machine learning algorithms for efficient water quality prediction
Water is an essential resource for human existence. In fact, more than 60% of the human
body is made up of water. Our bodies consume water in every cell, in the different organisms …
body is made up of water. Our bodies consume water in every cell, in the different organisms …
A deep learning-enabled IoT framework for early hypoxia detection in aqua water using light weight spatially shared attention-LSTM network
PG Arepalli, KJ Naik - The journal of Supercomputing, 2024 - Springer
Dissolved oxygen (DO) is a critical factor in maintaining healthy aquatic ecosystems,
including aquaculture ponds. Low DO levels can lead to hypoxia conditions, which are …
including aquaculture ponds. Low DO levels can lead to hypoxia conditions, which are …
An improved graph convolutional network with feature and temporal attention for multivariate water quality prediction
Q Ni, X Cao, C Tan, W Peng, X Kang - Environmental Science and …, 2023 - Springer
The analysis and prediction of water quality are of great significance to water quality
management and pollution control. In general, current water quality prediction methods are …
management and pollution control. In general, current water quality prediction methods are …
Efficient data-driven machine learning models for water quality prediction
Water is a valuable, necessary and unfortunately rare commodity in both develo** and
developed countries all over the world. It is undoubtedly the most important natural resource …
developed countries all over the world. It is undoubtedly the most important natural resource …
Application of classification machine learning algorithms for characterizing nutrient transport in a clay plain agricultural watershed
Excess nutrients in surface water and groundwater can lead to water quality deterioration in
available water resources. Thus, the classification of nutrient concentrations in water …
available water resources. Thus, the classification of nutrient concentrations in water …
Reconstructing daily discharge in a megadelta using machine learning techniques
In this study, six machine learning (ML) models, namely, random forest (RF), Gaussian
process regression (GPR), support vector regression (SVR), decision tree (DT), least …
process regression (GPR), support vector regression (SVR), decision tree (DT), least …
Research on a multiparameter water quality prediction method based on a hybrid model
Z Zheng, H Ding, Z Weng, L Wang - Ecological Informatics, 2023 - Elsevier
Watershed water quality monitoring is of great significance in the protection and
management of water environments. Because existing water quality prediction algorithms …
management of water environments. Because existing water quality prediction algorithms …
[HTML][HTML] Overview of the Research Status of Intelligent Water Conservancy Technology System
Q Li, Z Ma, J Li, W Li, Y Li, J Yang - Applied Sciences, 2024 - mdpi.com
A digital twin is a new trend in the development of the current smart water conservancy
industry. The main research content of intelligent water conservancy is clarified. This paper …
industry. The main research content of intelligent water conservancy is clarified. This paper …