A review of deep learning and machine learning techniques for hydrological inflow forecasting
SD Latif, AN Ahmed - Environment, Development and Sustainability, 2023 - Springer
Conventional machine learning models have been widely used for reservoir inflow and
rainfall prediction. Nowadays, researchers focus on a new computing architecture in the …
rainfall prediction. Nowadays, researchers focus on a new computing architecture in the …
Ensuring a generalizable machine learning model for forecasting reservoir inflow in Kurdistan region of Iraq and Australia
SD Latif, AN Ahmed - Environment, Development and Sustainability, 2024 - Springer
Correct inflow prediction is a critical non-engineering measure for ensuring flood control and
increasing water supply efficiency. In addition, accurate inflow prediction can offer reservoir …
increasing water supply efficiency. In addition, accurate inflow prediction can offer reservoir …
A novel stacked long short-term memory approach of deep learning for streamflow simulation
Rainfall-Runoff simulation is the backbone of all hydrological and climate change studies.
This study proposes a novel stochastic model for daily rainfall-runoff simulation called …
This study proposes a novel stochastic model for daily rainfall-runoff simulation called …
Hybrids of machine learning techniques and wavelet regression for estimation of daily solar radiation
As a primary input in meteorology, the accuracy of solar radiation simulations affects
hydrological, climatological, and agricultural studies and sustainable development practices …
hydrological, climatological, and agricultural studies and sustainable development practices …