Neuro-ensemble for air quality prediction

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DC Field	Value	Language
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
Appears in Collections:	Department of Civil Engineering

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