Inteligencia artificial aplicada a la predicción de inundaciones: Una revisión sistemática bajo el enfoque PRISMA 2020

Aurora Magdalena Gaibor Garófalo

Resumen


La creciente frecuencia e intensidad de inundaciones a nivel global, impulsada por el cambio climático y la expansión urbana no planificada, ha generado una necesidad urgente de métodos predictivos más eficientes. En este contexto, la inteligencia artificial (IA) se ha consolidado como una herramienta importante en el modelado y la predicción de eventos hidrometereológicos extremos.  El presente estudio realiza una revisión sistemática de literatura, basada en el protocolo PRISMA 2020, con el objetivo de analizar las principales tendencias científicas en el uso de algoritmos de IA para la predicción de inundaciones, la búsqueda se efectuó en las bases de datos Scopus, Web of Science y ScienceDirect. En análisis bibliométrico permitió identificar los modelos más empleados, las regiones con mayor producción científica y las revistas más influyentes. Los resultados evidencian un notable crecimiento en esta línea de investigación, destacando la proliferación de modelos híbridos, redes neuronales y enfoques de aprendizaje automático aplicados a contextos de alto riesgo climático.


Palabras clave


Inteligencia artificial; predicción de inundaciones; modelos híbridos; aprendizaje automático; riesgo climático.

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Referencias


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DOI: https://doi.org/10.23857/pc.v10i11.10747

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