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The factors influencing solar energy power generation include geographic location, solar radiation, weather conditions, …
In this study, a novel hybrid approach that integrates the evolutionary algorithm and mode decomposition into a radial b…
solar power systems are efficient and cost-effective. Accurate predictions can help power companies better manage their …
This study proposes the Extreme Gradient Boosting-based Solar Photovoltaic Power Generation Prediction (XGB-SPPGP) model…
An empirical study is carried out using real-world PV generation data, and the results are compared with popular gradien…
In this paper, a comprehensive study using ML and XAI methods to forecast solar generation has been presented. The main …
This research explores advanced machine learning (ML) and deep learning (DL) models, focusing on long short-term memory …
This paper focuses on identifying daily photovoltaic power production patterns to gain new knowledge of the generation p…
The NCPO algorithm''s optimization performance is assessed using IEEE public datasets, followed by the application of th…
In this paper, the power generation with a solar plant is forecasted by predicting the future weather generation using m…
This study contributes to the growing body of research on solar energy forecasting by:-Demonstrating the application and…
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