Modelado de series climatológicas mediante una red neuronal artificial

Jesús Palazón González

Spain

Universidad de Córdoba

Adela García Guzmán

Spain

Universidad de Córdoba

Enviado: 06-05-2014

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Aceptado:

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Publicado: 31-03-2004

DOI: https://doi.org/10.4995/ia.2004.2521
Datos de financiación

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Palabras clave:

Intensidad de la lluvia, Dependencia de la intensidad y duración de la lluvia, Red neuronal artificial, Términos de error en una red neuronal artificial

Agencias de apoyo:

Esta investigación no contó con financiación

Resumen:

Se ha desarrollado un modelo de red neuronal para caracterizar series meteorológicas que son difíciles de modelar con los métodos clásicos de inferencia estadística. Concretamente, se ha utilizado la red neuronal para cuantificar la relación intensidad – duración de la lluvia, variables que se encuentran interrelacionadas de una forma muy imprecisa. El modelo contiene funciones de transferencia no lineales e incluye términos de naturaleza estadística en la función de error. Para estimar los parámetros de la red neuronal se ha desarrollado un algoritmo de aprendizaje adaptado a funciones de error no derivables.
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