Solar Power Forecasting using Stacking Ensemble Models with Bayesian Meta-Learning
Author:
Affiliation:
1. School of Environment Resources and Development Asian Institute of Technology,Department of Energy, Environment and Climate Change,Thailand
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10306338/10306339/10308202.pdf?arnumber=10308202
Reference24 articles.
1. Comparison of Support Vector Machine and Extreme Gradient Boosting for predicting daily global solar radiation using temperature and precipitation in humid subtropical climates: A case study in China
2. Study on short-term photovoltaic power prediction model based on the Stacking ensemble learning
3. Investigating the performance of support vector machine and artificial neural networks in predicting solar radiation on a tilted surface: Saudi Arabia case study
4. Ensemble models for solar power forecasting—a weather classification approach
5. Multilayer Perceptron based Photovoltaic Forecasting for Rooftop PV Applications in Smart Grid;parvez;Southeast Con,2020
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1. Assessing Machine Learning Approaches for Photovoltaic Energy Prediction in Sustainable Energy Systems;IEEE Access;2024
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