Spatially adaptive machine learning models for predicting water quality in Hong Kong
Q Wang, Z Li, J Cai, M Zhang, Z Liu, Y Xu, R Li - Journal of Hydrology, 2023 - Elsevier
Water quality prediction in the spatially heterogeneous environment is challenging as the
importance of water quality parameters (WQPs) and the performance of prediction models …
importance of water quality parameters (WQPs) and the performance of prediction models …
Using machine learning models for predicting the water quality index in the La Buong River, Vietnam
For effective management of water quantity and quality, it is absolutely essential to estimate
the pollution level of the existing surface water. This case study aims to evaluate the …
the pollution level of the existing surface water. This case study aims to evaluate the …
Prediction of long-term water quality using machine learning enhanced by Bayesian optimisation
Water quality assessment is critical to better recognise the importance of water in human
society. In this study, a new framework to predict long-term water quality is proposed by …
society. In this study, a new framework to predict long-term water quality is proposed by …
Groundwater quality assessment using machine learning models: a comprehensive study on the industrial corridor of a semi-arid region
L Krishnamoorthy, VR Lakshmanan - Environmental Science and …, 2024 - Springer
Water plays a significant role in sustaining the lives of humans and other living organisms.
Groundwater quality analysis has become inevitable, because of increased contamination of …
Groundwater quality analysis has become inevitable, because of increased contamination of …
Designing efficient and sustainable predictions of water quality indexes at the regional scale using machine learning algorithms
Water quality and scarcity are key topics considered by the Sustainable Development Goals
(SDGs), institutions, policymakers and stakeholders to guarantee human safety, but also …
(SDGs), institutions, policymakers and stakeholders to guarantee human safety, but also …
A multidisciplinary approach for evaluating spatial and temporal variations in water quality
The primary goal of this study is to investigate the classification capability of several artificial
intelligence techniques, including the decision tree (DT), multilayer perceptron (MLP) …
intelligence techniques, including the decision tree (DT), multilayer perceptron (MLP) …
Machine learning methods for better water quality prediction
In any aquatic system analysis, the modelling water quality parameters are of considerable
significance. The traditional modelling methodologies are dependent on datasets that …
significance. The traditional modelling methodologies are dependent on datasets that …
Coastal groundwater quality prediction using objective-weighted WQI and machine learning approach
The water quality index (WQI) is a globally accepted guideline to indicate the water quality
standard of any groundwater resource. Water levels in existing groundwater sources are …
standard of any groundwater resource. Water levels in existing groundwater sources are …
Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index
In recent decades, various conventional techniques have been formulated around the world
to evaluate the overall water quality (WQ) at particular locations. In the present study, back …
to evaluate the overall water quality (WQ) at particular locations. In the present study, back …
Assessing and predicting water quality index with key water parameters by machine learning models in coastal cities, China
The water quality index (WQI) is a widely used tool for comprehensive assessment of river
environments. However, its calculation involves numerous water quality parameters, making …
environments. However, its calculation involves numerous water quality parameters, making …