SciELO - Scientific Electronic Library Online

 
vol.19 número3Herramienta Computacional para la Enseñanza de la Evaluación del Campo Eléctrico en Instalaciones IndustrialesDesarrollo de una Herramienta Software para la Vista de Información de la Arquitectura CIMOSA índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

Compartir


Información tecnológica

versión On-line ISSN 0718-0764

Resumen

GARCIA, Ignacio; MARBAN, Alonso; TENORIO, Yenisse M  y  RODRIGUEZ, José G. Ozone Concentration Forecast in Guadalajara-Mexico using Artificial Neuronal Networks. Inf. tecnol. [online]. 2008, vol.19, n.3, pp.89-96. ISSN 0718-0764.  http://dx.doi.org/10.4067/S0718-07642008000300013.

A forecasting model to predict the maximum ozone concentration in a specific day in the Metropolitan Area of Guadalajara-Mexico was developed. An Artificial Neuronal Network fed with six meteorological variables and three chemicals was used. Nodes in the hidden layer were varying in a number among 12 and 15. The transfer functions were log-sigmoid for the hidden layer and linear for the output layer. For the network training the Levenberg-Marquardt algorithm with historical dates from 1999 to 2004. Data for 2005 were used to evaluate the predictive capabilities of the trained network, evaluating the quality of the air at three levels: good, moderate, and unhealthy. The model presented global efficiencies of around 50%, reaching and 65% for high ozone concentrations.

Palabras clave : artificial neuronal network; air quality; algorithm; forecasting; ozone.

        · resumen en Español     · texto en Español     · Español ( pdf )

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons