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Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …
sustainability of water resources. The literature has shown great potential for nature-inspired …
Opportunities, challenges, and benefits of AI innovation in government services: a review
K Alhosani, SM Alhashmi - Discover Artificial Intelligence, 2024 - Springer
Artificial intelligence (AI) has emerged as an excellent tool across multiple industries and
holds great promise for the government, society, and economy. However, the absence of a …
holds great promise for the government, society, and economy. However, the absence of a …
The viability of extended marine predators algorithm-based artificial neural networks for streamflow prediction
Precise streamflow prediction is necessary for better planning and managing available
water and future water resources, especially for high altitude mountainous glacier melting …
water and future water resources, especially for high altitude mountainous glacier melting …
Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR …
Agriculture, meteorological, and hydrological drought is a natural hazard which affects
ecosystems in the central India of Maharashtra state. Due to limited historical data for …
ecosystems in the central India of Maharashtra state. Due to limited historical data for …
Long lead-time daily and monthly streamflow forecasting using machine learning methods
Long lead-time streamflow forecasting is of great significance for water resources planning
and management in both the short and long terms. Despite of some studies using machine …
and management in both the short and long terms. Despite of some studies using machine …
Streamflow forecasting using extreme gradient boosting model coupled with Gaussian mixture model
L Ni, D Wang, J Wu, Y Wang, Y Tao, J Zhang, J Liu - Journal of Hydrology, 2020 - Elsevier
The establishment of an accurate and reliable forecasting model is important for water
resource planning and management. In this study, we developed a hybrid model (namely …
resource planning and management. In this study, we developed a hybrid model (namely …
Generating ensemble streamflow forecasts: A review of methods and approaches over the past 40 years
Ensemble forecasting applied to the field of hydrology is currently an established area of
research embracing a broad spectrum of operational situations. This work catalogs the …
research embracing a broad spectrum of operational situations. This work catalogs the …
Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting
G Zuo, J Luo, N Wang, Y Lian, X He - Journal of Hydrology, 2020 - Elsevier
Reliable and accurate streamflow forecasting is vital for water resource management. Many
streamflow prediction studies have demonstrated the excellent prediction ability of …
streamflow prediction studies have demonstrated the excellent prediction ability of …
An overview of flood concepts, challenges, and future directions
This review provides a broad overview of the current state of flood research, current
challenges, and future directions. Beginning with a discussion of flood-generating …
challenges, and future directions. Beginning with a discussion of flood-generating …
Fractionation of dyes/salts using loose nanofiltration membranes: Insight from machine learning prediction
Wastewater (WW) served as the crucial indicator for sustainable development, human
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …
health, and the ecosystem. Nanofiltration (NF) membranes are efficient in contaminants, dye …