Publicado dic 1, 2010



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Juan David Velásquez H.

Carlos Jaime Franco C

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Resumen

En este artículo se pronostica la variación porcentual del Índice de Precios al


Consumidor en Colombia usando una red neuronal artificial. El modelo obtenido,


una red neuronal tipo perceptrón multicapa, es capaz de capturar el ciclo


estacional presente en los datos usando sólo los datos pasados, como entradas


a la red neuronal, y no es necesario incluir variables ficticias que representen


dicha componente estructural. La precisión de esta aproximación es mejor que


la obtenida por otros modelos presentados en la literatura, incluidos aquellos


con suavizaciones exponenciales, aproximaciones a modelos SARIMA y otras


configuraciones de redes neuronales.

Keywords

prediction, non-linear models, macroeconomics, SARIMA, exponential smoothingprevisão, modelos não lineares, macro-economia, SARIMA, suavizado exponencialpredicción, modelos no lineales, macroeconomía, SARIMA, suavizado exponencial

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Cómo citar
Velásquez H., J. D., & Franco C, C. J. (2010). Nota sobre la predicción del Índice de Precios al Consumidor usando redes neuronales artificiales. Cuadernos De Administración, 23(41). https://doi.org/10.11144/Javeriana.cao23-41.nspi
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