| dc.contributor.author | Barai, Sudhir Kumar | |
| dc.date.accessioned | 2021-11-27T04:13:10Z | |
| dc.date.available | 2021-11-27T04:13:10Z | |
| dc.date.issued | 2002 | |
| dc.identifier.uri | https://repository.lboro.ac.uk/articles/Neuro-ensemble_for_air_quality_prediction/9588167/files/17227241.pdf | |
| dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/3661 | |
| dc.description.abstract | The present study investig; ttes the advantage of ensemble of neural networks (Haykin, 2000) for forecasting the air pollution. The aim is to find accurate air quality predictors, which can work with low number of data sets and should be robust enough to handle data with noise and errors | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Loughborough University | en_US |
| dc.subject | Civil Engineering | en_US |
| dc.subject | Air pollutants | en_US |
| dc.subject | Air Quality | en_US |
| dc.title | Neuro-ensemble for air quality prediction | en_US |
| dc.type | Other | en_US |
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