NEURAL NETWORKS FOR AIR POLLUTION NOWCASTING
This work illustrates the use and some results of artificial neural networks (ANNs) for data quality control of air pollutants. ANNs are applied to the short-term predicting of air pollutant concentrations in urban areas. Observed versus predicted data are compared to test the efficacy of ANNs in simulating environmental processes. Statistical analysis is used for choice of neural structure. The model is validated on original data.
Document Type: Research Article
Affiliations: Institute of Control and System Research, Bulgarian Academy of Sciences, Sofia, Bulgaria
Publication date: 01 July 2006
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