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Combining a deep learning model with multivariate empirical mode decomposition for hourly global horizontal irradiance forecasting
Accurate and reliable global horizontal irradiance forecasting is one of the solutions for the
associated problems with grid-integrated PV plants. This study proposes a novel hybrid …
associated problems with grid-integrated PV plants. This study proposes a novel hybrid …
A robust regressor model for estimating solar radiation using an ensemble stacking approach based on machine learning
Of late, with the rapid advancement in solar power generation, some difficulties have
cropped up due to solar intermittency, necessitating an accurate forecast of Global …
cropped up due to solar intermittency, necessitating an accurate forecast of Global …
Short-term wind power prediction method based on multivariate signal decomposition and RIME optimization algorithm
Accurate characterization of the dynamics of wind power systems under highly unstable
conditions is essential for short-term wind power forecasting. Multivariate factors, such as …
conditions is essential for short-term wind power forecasting. Multivariate factors, such as …
Forecasting hourly day-ahead solar photovoltaic power generation by assembling a new adaptive multivariate data analysis with a long short-term memory network
Accurate multi-step PV power forecasting is a challenging task because of complex time
series and error buildup in muti-step forecasts. This work is based on develo** a …
series and error buildup in muti-step forecasts. This work is based on develo** a …
Mode decomposition based large margin distribution machines for sediment load prediction
Precise suspended sediment load (SSL) prediction is essential for irrigation, hydropower
and river management practices. But due to some external factors such as high altitude …
and river management practices. But due to some external factors such as high altitude …
Machine learning-based prediction and mathematical optimization of Capecitabine solubility through the supercritical CO2 system
This work represents development of computational intelligence models for assessment of
estimating solubility/bioavailability of orally-taken drugs in SCF (supercritical fluid). The SCF …
estimating solubility/bioavailability of orally-taken drugs in SCF (supercritical fluid). The SCF …
[HTML][HTML] Accurate Forecasting of Global Horizontal Irradiance in Saudi Arabia: A Comparative Study of Machine Learning Predictive Models and Feature Selection …
The growing interest in solar energy stems from its potential to reduce greenhouse gas
emissions. Global horizontal irradiance (GHI) is a crucial determinant of the productivity of …
emissions. Global horizontal irradiance (GHI) is a crucial determinant of the productivity of …
Improved second-harmonic imaging of ultrasound contrast agents using VGG-style network with adaptively decomposed ultrasound RF signals
J Zhu, Y Zhang, B He, Z Li, L **ong, X Lang - Biomedical Signal Processing …, 2024 - Elsevier
Accurately distinguishing between ultrasound contrast agents (UCAs) and tissue
components is crucial for suppressing the influence of tissue and enhancing the second …
components is crucial for suppressing the influence of tissue and enhancing the second …
Proposing an innovative model for solar irradiance and wind speed forecasting
X Liu - Applied Thermal Engineering, 2025 - Elsevier
To optimize hydrogen refueling stations (HRS), which are reliant on renewable energy
sources such as solar and wind, it is imperative to have precise predictions of wind speed …
sources such as solar and wind, it is imperative to have precise predictions of wind speed …
Evaluating landslide susceptibility and landscape changes due to road expansion using optimized machine learning
Abstract The Garhwal and Kumaun regions of the Himalayas of India have experienced
rapid urbanisation due to the expansion of the national highway (NH-58) in Uttarakhand …
rapid urbanisation due to the expansion of the national highway (NH-58) in Uttarakhand …