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Poster 18 Principal component and multiple linear regressions to predict ozone concentrations

Title
Poster 18 Principal component and multiple linear regressions to predict ozone concentrations
Type
Another Publication in an International Scientific Journal
Year
2007
Authors
Sousa, SIV
(Author)
FEUP
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Martins, FG
(Author)
FEUP
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Pires, J
(Author)
Other
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Alvim Ferraz, MCM
(Author)
Other
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Pereira, MC
(Author)
FEUP
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Journal
Vol. 33
Pages: 790-792
ISSN: 1474-8177
Publisher: Elsevier B.V.
Indexing
Publicação em ISI Web of Knowledge ISI Web of Knowledge
Publicação em Scopus Scopus - 0 Citations
Other information
Authenticus ID: P-008-NT3
Abstract (EN): The aim of this study was: (i) to predict next day hourly ozone concentrations, for an urban site with traffic influence located at Oporto, by applying principal component regression (PCR); and (ii) comparing PCR with multiple linear regression (MLR). The use of principal components as inputs in the models improved the O3 concentrations prediction.
Language: English
Type (Professor's evaluation): Scientific
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