La inteligencia artificial en la predicción de la temperatura ambiental y del suelo en Ecuador
DOI:
https://doi.org/10.31637/epsir-2025-550Palabras clave:
Series de tiempo, temperatura suelo, temperatura ambiente, inteligencia artificial, pronósticos, algoritmos supervisados, Ecuador, ARIMAResumen
Introducción: El estudio tuvo como objetivo principal analizar la probabilidad y predicción para la temperatura ambiental y el suelo en la zona costera de Manabí en Ecuador. Metodología: La metodología hace uso de series de tiempo Box Jenkins ARIMA y de comparación de medias. Los datos se midieron a las 07:00 am, 12:00 pm y 18:00pm, iniciando en enero de 2015 hasta diciembre del 2020. Los datos se analizaron y procesaron con la ayuda de la inteligencia artificial incorporada al software RStudio. Resultados: Los resultados, evidencian que la temperatura del suelo está correlacionada con la temperatura ambiental. Discusión: Las pruebas de bondades de ajuste para los coeficientes y supuestos validaron el modelo ARIMA observado y esperado. Además, los criterios AIC y BIC se utilizaron para escoger el mejor modelo predictivo. Conclusiones: En conclusión, la inteligencia artificial identificó que la predicción de las temperaturas ambiental y del suelo son simuladas adecuadamente a través de un modelo ARIMA(0,1,1)(0,1,1)[12], con componentes de tendencia y estacionalidad; afirmando un modelo de series de tiempo no estacionario. Se llega a determinar que, la temperatura tiene una pequeña variabilidad por cada periodo de tiempo, pero en aumento, y en lo posterior probablemente este factor climático se convierta en un determinante del calentamiento global.
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Derechos de autor 2024 Ángel Ramón Sabando-García, Mikel Ugando Peñate; Reinaldo Armas Herrera (Autor de Correspondencia); Angel Alexander Higuerey Gómez, Néstor Leopoldo Tarazona Meza, Pierina D'Elia Di Michele, Elvia Rosalía Inga Llanez
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