Scholarlink

This project aims to develop a methodology for predicting solar radiation in San Francisco Pichátaro, a community in the municipality of Tingambato, Michoacán, Mexico. This community lies within the Purépecha indigenous zone. The project utilized two databases: one from a solarimetric station in the area and the other from the Solcast platform, which provides access to solar irradiance and other pertinent meteorological variables. Rigorous data cleansing and analysis procedures were implemented to ensure data quality and compatibility. Subsequently, both linear and decision tree regression models were applied to the refined and prepared data to forecast solar radiation.

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Machine Learning Algorithms for Solar Irradiance Forecasting in a Rural Community in Michoacán, Mexico

  • 会议论文

  • 发表日期：

    2025年

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  • Ana Martínez-Gámez,
  • Heberto Ferreira-Medina,
  • Luis Bernardo López-Sosa,
  • Sayra Orozco,
  • Mario Morales-Máximo,
  • Carlos A. García,
  • Michel Rivero

摘要

This project aims to develop a methodology for predicting solar radiation in San Francisco Pichátaro, a community in the municipality of Tingambato, Michoacán, Mexico. This community lies within the Purépecha indigenous zone. The project utilized two databases: one from a solarimetric station in the area and the other from the Solcast platform, which provides access to solar irradiance and other pertinent meteorological variables. Rigorous data cleansing and analysis procedures were implemented to ensure data quality and compatibility. Subsequently, both linear and decision tree regression models were applied to the refined and prepared data to forecast solar radiation.