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 …

[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 …

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 …

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 …

[HTML][HTML] Variability in runoff and responses to land and oceanic parameters in the source region of the Indus River

A Hussain, J Cao, S Ali, W Ullah, S Muhammad… - Ecological …, 2022 - Elsevier
Understanding the coherent variability of runoff in the Source Region of the Indus River
(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 …

A multivariate streamflow forecasting model by integrating improved complete ensemble empirical mode decomposition with additive noise, sample entropy, Gini …

H Apaydin, M Sibtain - Journal of Hydrology, 2021 - Elsevier
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 …

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 …

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 …

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 …