Palabras clave
Regresión
Algoritmo genético
Recocido simulado
Retropropagación
Optimización
Cómo citar
Resumen
Las Redes Neuronales Artificiales han ganado notoriedad en la aproximación de funciones uni y multivariadas debido a la alta capacidad de aproximación de este tipo de modelos. En este artículo se presenta una descripción de los modelos de regresión basados en redes neuronales junto con los algoritmos comúnmente utilizados para optimizarlos. El rendimiento de este tipo de modelo se ejemplifica mediante la aproximación de una función univariante que relaciona la fracción molar en la fase líquida de uno de los componentes de una mezcla de agua y acetona con su fracción molar en la fase de vapor. El rendimiento del modelo también se compara con el rendimiento de otros modelos basados en métodos de regresión clásicos utilizados para resolver el mismo problema. Al final del texto, se presenta el código PYTHON para crear el modelo de red neuronal discutido aquí.
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Derechos de autor 2021 Gabriel César Pereira, Rogério Custodio