Hydropower operation optimization using machine learning: A systematic review
J Bernardes Jr, M Santos, T Abreu, L Prado Jr… - AI, 2022 - mdpi.com
The optimal dispatch of hydropower plants consists of the challenge of taking advantage of
both available head and river flows. Despite the objective of delivering the maximum power …
both available head and river flows. Despite the objective of delivering the maximum power …
[HTML][HTML] Flood prediction with time series data mining: Systematic review
DK Hakim, R Gernowo, AW Nirwansyah - Natural Hazards Research, 2024 - Elsevier
The global community is continuously working to minimize the impact of disasters through
various actions, including earth surveying. For example, flood-prone areas must be …
various actions, including earth surveying. For example, flood-prone areas must be …
Forecasting oil production using ensemble empirical model decomposition based Long Short-Term Memory neural network
W Liu, WD Liu, J Gu - Journal of Petroleum Science and Engineering, 2020 - Elsevier
Oil production forecasting is an important means of understanding and effectively
developing reservoirs. Reservoir numerical simulation is the most mature and effective …
developing reservoirs. Reservoir numerical simulation is the most mature and effective …
A hybrid VMD-SVM model for practical streamflow prediction using an innovative input selection framework
E Meng, S Huang, Q Huang, W Fang, H Wang… - Water Resources …, 2021 - Springer
Some previous studies have proved that prediction models using traditional overall
decomposition sampling (ODS) strategy are unreasonable because the subseries obtained …
decomposition sampling (ODS) strategy are unreasonable because the subseries obtained …
[HTML][HTML] Variability in runoff and responses to land and oceanic parameters in the source region of the Indus River
Understanding the coherent variability of runoff in the Source Region of the Indus River
(SRIR) with the regional environmental parameters (precipitation, temperature, potential …
(SRIR) with the regional environmental parameters (precipitation, temperature, potential …
Drought management planning policy: from Europe to Spain
C Hervás-Gámez, F Delgado-Ramos - Sustainability, 2019 - mdpi.com
Climate change is anticipated to exacerbate the frequency, the intensity, and the duration of
droughts, especially in Mediterranean countries. This might lead to more serious water …
droughts, especially in Mediterranean countries. This might lead to more serious water …
A multivariate streamflow forecasting model by integrating improved complete ensemble empirical mode decomposition with additive noise, sample entropy, Gini …
Accurate and reliable streamflow forecasting is indispensable to deal with the dynamics of
streamflow parameters and for optimal use of water resources, flood, and drought control. In …
streamflow parameters and for optimal use of water resources, flood, and drought control. In …
Digital transformation of energy companies: A colombian case study
S Giraldo, D la Rotta, C Nieto-Londoño, RE Vásquez… - Energies, 2021 - mdpi.com
The United Nations established 17 Sustainable Development Goals (SDGs), and the
fulfillment of the 7th, defined as “Ensure access to affordable, reliable, sustainable, and …
fulfillment of the 7th, defined as “Ensure access to affordable, reliable, sustainable, and …
Monthly streamflow prediction in Amasya, Türkiye, using an integrated approach of a feedforward backpropagation neural network and discrete wavelet transform
OM KATİPOĞLU - Modeling Earth Systems and Environment, 2023 - Springer
Due to climate change and increasing demand for water, effective planning of water
resources is a current issue. Reliable and accurate streamflow prediction is of great …
resources is a current issue. Reliable and accurate streamflow prediction is of great …
Daily runoff forecasting using ensemble empirical mode decomposition and long short-term memory
R Yuan, S Cai, W Liao, X Lei, Y Zhang, Z Yin… - Frontiers in Earth …, 2021 - frontiersin.org
Hydrological series data are non-stationary and nonlinear. However, certain data-driven
forecasting methods assume that streamflow series are stable, which contradicts reality and …
forecasting methods assume that streamflow series are stable, which contradicts reality and …