Short-term multi-hour ahead country-wide wind power prediction for Germany using gated recurrent unit deep learning
In recent years, wind power has emerged as an important source of renewable energy.
When onshore and offshore wind farm regions are connected to the grid for power …
When onshore and offshore wind farm regions are connected to the grid for power …
Forecasting of solar radiation using different machine learning approaches
In this study, monthly solar radiation (SR) estimation was performed using five different
machine learning-based approaches. The models used are support vector machine …
machine learning-based approaches. The models used are support vector machine …
Comparison of hybrid machine learning methods for the prediction of short-term meteorological droughts of Sakarya Meteorological Station in Turkey
H Citakoglu, Ö Coşkun - Environmental Science and Pollution Research, 2022 - Springer
Drought is a harmful natural disaster with various negative effects on many aspects of life. In
this research, short-term meteorological droughts were predicted with hybrid machine …
this research, short-term meteorological droughts were predicted with hybrid machine …
Scenario-based automated data preprocessing to predict severity of construction accidents
Occupational accidents are common in the construction industry, therefore develo**
prediction models to detect high severe accidents would be useful. However, existing …
prediction models to detect high severe accidents would be useful. However, existing …
Pre-and post-dam river water temperature alteration prediction using advanced machine learning models
Dams significantly impact river hydrology by changing the timing, size, and frequency of low
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …
and high flows, resulting in a hydrologic regime that differs significantly from the natural flow …
Coordinated optimization on energy capture and torque fluctuation of wind turbines via variable weight NMPC with fuzzy regulator
D Song, Y Tu, L Wang, F **, Z Li, C Huang, E **a… - Applied Energy, 2022 - Elsevier
The main challenge in improving energy harvest faced by modern large-scale wind turbines
(WTs) comes from the fact that the blade rotor with the large inertia having a slow response …
(WTs) comes from the fact that the blade rotor with the large inertia having a slow response …
Prediction of the standardized precipitation index based on the long short-term memory and empirical mode decomposition-extreme learning machine models: The …
Ö Coşkun, H Citakoglu - Physics and Chemistry of the Earth, Parts A/B/C, 2023 - Elsevier
This research predicted the meteorological drought of Sakarya province in northwest Türkiye
using long short-term memory (LSTM). This deep learning algorithm has gained popularity …
using long short-term memory (LSTM). This deep learning algorithm has gained popularity …
An online-learning-enabled self-attention-based model for ultra-short-term wind power forecasting
Renewable wind power accounts for an increasing proportion of the smart grid nowadays.
The intermittent and fluctuating nature of wind renders wind power forecasting important …
The intermittent and fluctuating nature of wind renders wind power forecasting important …
The dynamic economic emission dispatch of the combined heat and power system integrated with a wind farm and a photovoltaic plant
D Zou, D Gong, H Ouyang - Applied Energy, 2023 - Elsevier
Two renewable energies are included in the combined heat and power (CHP) system to
optimize its energy configuration, and they are wind power generation and photovoltaic …
optimize its energy configuration, and they are wind power generation and photovoltaic …
General and regional cross-station assessment of machine learning models for estimating reference evapotranspiration
Significant research has been done on estimating reference evapotranspiration (ET 0) from
limited climatic measurements using machine learning (ML) to facilitate the acquirement of …
limited climatic measurements using machine learning (ML) to facilitate the acquirement of …