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This study focuses on the prediction of solar illuminance as a function of temperature and humidity using machine learning models. Meteorological data and solar illuminance measurements were collected from several locations over a specific time period. These data were used to train and evaluate several regression models, which were The results showed that the multiple linear regression model provided accurate predictions of solar illuminance as a function of weather conditions. This approach has important applications in solar energy management.

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Reliability Calculation of a Neural Network for Voltage Prediction in Solar Panels Based on Temperature, Humidity, UV, Current, and Illuminance

  • 会议论文

  • 发表日期：

    2025年

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  • Marco Fidel Mayta Quispe,
  • Elwis Wagner Choque Huacasi,
  • Fred Torres Cruz

摘要

This study focuses on the prediction of solar illuminance as a function of temperature and humidity using machine learning models. Meteorological data and solar illuminance measurements were collected from several locations over a specific time period. These data were used to train and evaluate several regression models, which were The results showed that the multiple linear regression model provided accurate predictions of solar illuminance as a function of weather conditions. This approach has important applications in solar energy management.