HERisk and statistical clustering integrated for health risk modelling of PTEs in natural water resources for drinking and sanitary uses
Potentially toxic elements (PTEs) are well-known for exposing living organisms and humans
to different levels of risk. The present study aimed to evaluate the extent of exposure to …
to different levels of risk. The present study aimed to evaluate the extent of exposure to …
A new benchmark on machine learning methodologies for hydrological processes modelling: a comprehensive review for limitations and future research directions
ZM Yaseen - Knowledge-Based Engineering …, 2023 - … journals.publicknowledgeproject.org
The best practice of watershed management is through the understanding of the
hydrological processes. As a matter of fact, hydrological processes are highly associated …
hydrological processes. As a matter of fact, hydrological processes are highly associated …
Development of integrative data intelligence models for thermo-economic performances prediction of hybrid organic rankine plants
Computer aid models such as machine learning (ML) are massively observed to be
successfully applied in different engineering-related domains. The current research was …
successfully applied in different engineering-related domains. The current research was …
Robust drought forecasting in Eastern Canada: Leveraging EMD-TVF and ensemble deep RVFL for SPEI index forecasting
Drought stands as a highly perilous natural catastrophe that impacts numerous facets of
human existence. Drought data is nonstationary and noisy, posing challenges for accurate …
human existence. Drought data is nonstationary and noisy, posing challenges for accurate …
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 …
[HTML][HTML] Quantitative improvement of streamflow forecasting accuracy in the Atlantic zones of Canada based on hydro-meteorological signals: A multi-level advanced …
Developing reliable streamflow forecasting models is critical for hydrological tasks such as
improving water resource management, analyzing river patterns, and flood forecasting. In …
improving water resource management, analyzing river patterns, and flood forecasting. In …
Forecasting for Haditha reservoir inflow in the West of Iraq using Support Vector Machine (SVM)
OA Mahmood, SO Sulaiman, D Al-Jumeily - PloS one, 2024 - journals.plos.org
Accurate inflow forecasting is an essential non-engineering strategy to guarantee flood
management and boost the effectiveness of the water supply. As inflow is the primary …
management and boost the effectiveness of the water supply. As inflow is the primary …
Spatial analysis and predictive modeling of energy poverty: insights for policy implementation
Understanding and alleviating energy poverty is critical for sustainable development. This
study harnesses a suite of Machine Learning (ML) algorithms to predict Multidimensional …
study harnesses a suite of Machine Learning (ML) algorithms to predict Multidimensional …
[HTML][HTML] LSTM Model Integrated Remote Sensing Data for Drought Prediction: A Study on Climate Change Impacts on Water Availability in the Arid Region
Climate change is one of the trending terms in the world nowadays due to its profound
impact on human health and activity. Extreme drought events and desertification are some of …
impact on human health and activity. Extreme drought events and desertification are some of …
[HTML][HTML] Groundwater level prediction using an improved SVR model integrated with hybrid particle swarm optimization and firefly algorithm
The demand for water resources has increased due to rapid increase of metropolitan areas
brought on by growth in population and industrialisation. In addition, the groundwater …
brought on by growth in population and industrialisation. In addition, the groundwater …