FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2904068143> ?p ?o ?g. }

• W2904068143 endingPage "49" @default.
• W2904068143 startingPage "40" @default.
• W2904068143 abstract "Abstract Missing data from air quality datasets is a common problem, but is much more severe in small cities or localities. This poses a great challenge for environmental epidemiology as high exposures to pollutants worldwide occur in these settings and gaps in datasets hinder health studies that could later inform local and international policies. Here, we propose the use of imputation methods as a tool to reconstruct air quality datasets and have applied this approach to an air quality dataset in Temuco, a mid-size city in Chile as a case-study. We attempted to reconstruct the database comparing five approaches: mean imputation, conditional mean imputation, K-Nearest Neighbor imputation, multiple imputation and Bayesian Principal Component Analysis imputation. As a base for the imputation methods, linear regression models were fitted for PM2.5 against other air quality and meteorological variables. Methods were challenged against validation sets where data was removed artificially. Imputation methods were able to reconstruct the dataset with good performance in terms of completeness, errors, and bias, even when challenged against the validations sets. The performance improved when including covariates from a second monitoring station in Temuco. K-Nearest Neighbor imputation showed slightly better performance than multiple imputation for error (25% vs. 27%) and bias (2.1% vs. 3.9%), but presented lower completeness (70% vs. 100%). In summary, our results show that the imputation methods can be a useful tool in reconstructing air quality datasets in a real-life situation." @default.
• W2904068143 created "2018-12-22" @default.
• W2904068143 creator A5031691523 @default.
• W2904068143 creator A5045273804 @default.
• W2904068143 creator A5045402989 @default.
• W2904068143 creator A5052564163 @default.
• W2904068143 creator A5059426911 @default.
• W2904068143 creator A5072532866 @default.
• W2904068143 creator A5076017545 @default.
• W2904068143 creator A5085251881 @default.
• W2904068143 date "2019-03-01" @default.
• W2904068143 modified "2023-10-01" @default.
• W2904068143 title "Use of data imputation tools to reconstruct incomplete air quality datasets: A case-study in Temuco, Chile" @default.
• W2904068143 cites W1964065566 @default.
• W2904068143 cites W1966635046 @default.
• W2904068143 cites W1987047286 @default.
• W2904068143 cites W1993220086 @default.
• W2904068143 cites W2006816310 @default.
• W2904068143 cites W2007560565 @default.
• W2904068143 cites W2009808798 @default.
• W2904068143 cites W2024806077 @default.
• W2904068143 cites W2031459800 @default.
• W2904068143 cites W2047627251 @default.
• W2904068143 cites W2065974896 @default.
• W2904068143 cites W2078965693 @default.
• W2904068143 cites W2130089609 @default.
• W2904068143 cites W2135089494 @default.
• W2904068143 cites W2139572631 @default.
• W2904068143 cites W2146848957 @default.
• W2904068143 cites W2156267802 @default.
• W2904068143 cites W2166561686 @default.
• W2904068143 cites W2167942713 @default.
• W2904068143 cites W2168089684 @default.
• W2904068143 cites W2595190334 @default.
• W2904068143 cites W2793601091 @default.
• W2904068143 cites W293480591 @default.
• W2904068143 cites W4211101039 @default.
• W2904068143 doi "https://doi.org/10.1016/j.atmosenv.2018.11.053" @default.
• W2904068143 hasPublicationYear "2019" @default.
• W2904068143 type Work @default.
• W2904068143 sameAs 2904068143 @default.
• W2904068143 citedByCount "28" @default.
• W2904068143 countsByYear W29040681432019 @default.
• W2904068143 countsByYear W29040681432020 @default.
• W2904068143 countsByYear W29040681432021 @default.
• W2904068143 countsByYear W29040681432022 @default.
• W2904068143 countsByYear W29040681432023 @default.
• W2904068143 crossrefType "journal-article" @default.
• W2904068143 hasAuthorship W2904068143A5031691523 @default.
• W2904068143 hasAuthorship W2904068143A5045273804 @default.
• W2904068143 hasAuthorship W2904068143A5045402989 @default.
• W2904068143 hasAuthorship W2904068143A5052564163 @default.
• W2904068143 hasAuthorship W2904068143A5059426911 @default.
• W2904068143 hasAuthorship W2904068143A5072532866 @default.
• W2904068143 hasAuthorship W2904068143A5076017545 @default.
• W2904068143 hasAuthorship W2904068143A5085251881 @default.
• W2904068143 hasBestOaLocation W29040681432 @default.
• W2904068143 hasConcept C105795698 @default.
• W2904068143 hasConcept C124101348 @default.
• W2904068143 hasConcept C126314574 @default.
• W2904068143 hasConcept C127413603 @default.
• W2904068143 hasConcept C153294291 @default.
• W2904068143 hasConcept C176217482 @default.
• W2904068143 hasConcept C205649164 @default.
• W2904068143 hasConcept C21547014 @default.
• W2904068143 hasConcept C24756922 @default.
• W2904068143 hasConcept C33923547 @default.
• W2904068143 hasConcept C39432304 @default.
• W2904068143 hasConcept C41008148 @default.
• W2904068143 hasConcept C58041806 @default.
• W2904068143 hasConcept C9357733 @default.
• W2904068143 hasConceptScore W2904068143C105795698 @default.
• W2904068143 hasConceptScore W2904068143C124101348 @default.
• W2904068143 hasConceptScore W2904068143C126314574 @default.
• W2904068143 hasConceptScore W2904068143C127413603 @default.
• W2904068143 hasConceptScore W2904068143C153294291 @default.
• W2904068143 hasConceptScore W2904068143C176217482 @default.
• W2904068143 hasConceptScore W2904068143C205649164 @default.
• W2904068143 hasConceptScore W2904068143C21547014 @default.
• W2904068143 hasConceptScore W2904068143C24756922 @default.
• W2904068143 hasConceptScore W2904068143C33923547 @default.
• W2904068143 hasConceptScore W2904068143C39432304 @default.
• W2904068143 hasConceptScore W2904068143C41008148 @default.
• W2904068143 hasConceptScore W2904068143C58041806 @default.
• W2904068143 hasConceptScore W2904068143C9357733 @default.
• W2904068143 hasFunder F4320320240 @default.
• W2904068143 hasFunder F4320334812 @default.
• W2904068143 hasFunder F4320335254 @default.
• W2904068143 hasFunder F4320338337 @default.
• W2904068143 hasLocation W29040681431 @default.
• W2904068143 hasLocation W29040681432 @default.
• W2904068143 hasOpenAccess W2904068143 @default.
• W2904068143 hasPrimaryLocation W29040681431 @default.
• W2904068143 hasRelatedWork W1999846678 @default.
• W2904068143 hasRelatedWork W2574666645 @default.
• W2904068143 hasRelatedWork W2986875369 @default.
• W2904068143 hasRelatedWork W2997516437 @default.
• W2904068143 hasRelatedWork W3009008716 @default.

• next