[HTML][HTML] Short-term PV power forecasting using variational mode decomposition integrated with Ant colony optimization and neural network
S Netsanet, D Zheng, W Zhang, G Teshager - Energy Reports, 2022 - Elsevier
Abstract In this paper, Artificial Neural Network (ANN) is integrated with data processing,
input variable selection, and external optimization techniques to forecast the day ahead …
input variable selection, and external optimization techniques to forecast the day ahead …
Kernel learning for intra-hour solar forecasting with infrared sky images and cloud dynamic feature extraction
G Terrén-Serrano, M Martínez-Ramón - Renewable and Sustainable …, 2023 - Elsevier
Power grid operators incur additional costs to guarantee a reliable energy supply due to the
uncertainty of the energy generated by photovoltaic systems. These additional costs are …
uncertainty of the energy generated by photovoltaic systems. These additional costs are …
Selection of key features for PM2. 5 prediction using a wavelet model and RBF-LSTM
YC Chen, DC Li - Applied Intelligence, 2021 - Springer
PM2. 5 prediction has received much attention from researchers in recent years, as PM2. 5
has been proven to have a major impact on human health. High-precision PM2. 5 …
has been proven to have a major impact on human health. High-precision PM2. 5 …
Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression
Abstract Prediction of Total Cloud Cover (TCDC) from numerical weather simulation models,
such as Global Forecast System (GFS), can aid renewable energy engineers in monitoring …
such as Global Forecast System (GFS), can aid renewable energy engineers in monitoring …
Estimation of daily stage–discharge relationship by using data-driven techniques of a perennial river, India
Modeling the stage-discharge relationship in river flow is crucial in controlling floods,
planning sustainable development, managing water resources and economic development …
planning sustainable development, managing water resources and economic development …
Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India
This research was established to accurately forecast daily scale air quality index (AQI) which
is an essential environmental index for decision-making. Researchers have projected …
is an essential environmental index for decision-making. Researchers have projected …
Precise single step and multistep short-term photovoltaic parameters forecasting based on reduced deep convolutional stack autoencoder and minimum variance …
Accurate prediction of photovoltaic (PV) power can significantly alleviate energy crises.
However, the inherent randomness and intermittency of PV power pose challenges to the …
However, the inherent randomness and intermittency of PV power pose challenges to the …
The development of dissolved oxygen forecast model using hybrid machine learning algorithm with hydro-meteorological variables
Dissolved oxygen (DO) forecasting is essential for aquatic managers responsible for
maintaining ecosystem health and the management of water bodies affected by water …
maintaining ecosystem health and the management of water bodies affected by water …
Comparative Analysis Using Multiple Regression Models for Forecasting Photovoltaic Power Generation
Effective machine learning regression models are useful toolsets for managing and planning
energy in PV grid-connected systems. Machine learning regression models, however, have …
energy in PV grid-connected systems. Machine learning regression models, however, have …
Autoencoder-based improved deep learning approach for schizophrenic EEG signal classification
In this paper, deep-stacked error minimized extreme learning machine autoencoder
(DSEMELMAE) and sine–cosine monarch butterfly optimization-based minimum variance …
(DSEMELMAE) and sine–cosine monarch butterfly optimization-based minimum variance …