A  Neural Network Based Model For The Analysis Of

Carbon Monoxide Contamination  In The Urban

Area Of Rosario

B. Drozdowicz; S.J. Benz; A.S.M. Santa Cruz; N.J. Scenna

doi:10.2495/AIR970641

A Neural Network Based Model For The Analysis Of Carbon Monoxide Contamination In The Urban Area Of Rosario

Price

Free (open access)

Transaction

WIT Transactions on Ecology and the Environment

Volume

Pages

Published

1997

Size

726 kb

Paper DOI

10.2495/AIR970641

WIT Press

Author(s)

B. Drozdowicz, S.J. Benz, A.S.M. Santa Cruz & N.J. Scenna

Abstract

A neural network based model for estimating (hourly mean concentrations) carbon monoxide in the urban area of Rosario City, in Santa Fe, Argentine is presented. The data series of carbon monoxide and emission inventory is also a result of this work (up to now no data were reported for Rosario). It is based on a typical neural network architecture, e.g. Lawrence [5]. Several inputs like mean hourly traffic flux -segregating different type of vehicles-, wind speed and dire

Keywords

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Code

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