Neural network-based prediction model of ozone for Mexico City


Por: Ruiz-Suarez J.C., Mayora O.A., Smith-Perez R., Ruiz-Suarez L.G.

Publicada: 1 ene 1994
Resumen:
This paper describes current work for developing a short-term forecasting model for ozone in Mexico City. The structure of the model is based on a recently created paradigm, the Holographic Associative Memory (HAM). The HAM is able to store a large amount of daily patterns and address any of them in a efficient way. Preliminary results of ozone forecasting are reported and some important conclusions are drawn.

Filiaciones:
Ruiz-Suarez J.C.:
 Instituto Tecnologico y de Estudios, Superiores de Monterrey, Morelos, Mexico

Mayora O.A.:
 Instituto Tecnologico y de Estudios, Superiores de Monterrey, Morelos, Mexico

Smith-Perez R.:
 Instituto Tecnologico y de Estudios, Superiores de Monterrey, Morelos, Mexico

Ruiz-Suarez L.G.:
 Instituto Tecnologico y de Estudios, Superiores de Monterrey, Morelos, Mexico
ISSN: 0000184P
Editorial
Computational Mechanics Publ, Southampton, United Kingdom
Tipo de documento: Conference Paper
Volumen: 1 Número:
Páginas: 393-400

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