Modelación Univariante Prophet para el Pronóstico de Precipitaciones en Estaciones Meteorológicas de Tungurahua-Ecuador

Autores/as

DOI:

https://doi.org/10.59169/pentaciencias.v8i2.1803

Palabras clave:

Prophet; precipitaciones; pronóstico; áreas andinas

Resumen

El pronóstico de precipitaciones es una herramienta esencial para la gestión sostenible de los recursos hídricos. Este estudio aplica el modelo univariante Prophet para estimar precipitaciones diarias en 19 estaciones meteorológicas de la provincial de Tungurahua, Ecuador, a fin de generar información confiable que respalde la toma de decisiones en los sectores de infraestructura, agricultura y gestión ambiental. Se utilizaron series de tiempo diarias de precipitación para el entrenamiento y la validación del modelo, abarcando datos registrados entre 2013 y 2024. El modelo fue evaluado bajo tres segmentaciones de datos: 80-20%, 85-15% y 90-10% para entrenamiento y prueba, respectivamente. Además, se consideraron tanto los valores predeterminados de Prophet como la configuración de hiperparámetros encontrados mediante búsqueda por cuadrícula. El desempeño se evaluó mediante las métricas MAE y RMSE, cuyos valores oscilaron entre 1.0398 y 3.8012 mm y entre 1.8956 y 6.3168 mm, respectivamente, lo que evidencia una capacidad predictive adecuada en relación con el promedio de la precipitación diaria. A partir de los resultados obtenidos, se determinó que el modelo Prophet mejora su precisión al incrementarse el porcentaje de datos destinados al entrenamiento, alcanzando sus mejores desempeños con las divisiones 85-15% y 90-10% para entrenamiento y validación, respectivamente, utilizando la configuración de hiperparámetros determinada mediante búsqueda por cuadrícula.

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Citas

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Publicado

2026-05-01

Cómo citar

Anthony Zabala, Contreras-Vásquez , L. ., Pérez Maldonado , R. L. ., & Viscaíno-Cuzco , M. . (2026). Modelación Univariante Prophet para el Pronóstico de Precipitaciones en Estaciones Meteorológicas de Tungurahua-Ecuador. Revista Científica Arbitrada Multidisciplinaria PENTACIENCIAS, 8(2), 143–163. https://doi.org/10.59169/pentaciencias.v8i2.1803

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