Repository logo
 
Publication

Comparison of discriminant analysis methods: Application to occupational exposure to particulate matter

2016Conference object Restricted access
Simple item page
datacite.subject.sdg03:Saúde de Qualidadept_PT
datacite.subject.sdg17:Parcerias para a Implementação dos Objetivospt_PT
dc.contributor.authorRamos, Maria do Rosário
dc.contributor.authorCarolino, E.
dc.contributor.authorViegas, Carla
dc.contributor.authorViegas, Sandra
dc.date.accessioned2023-08-02T14:16:50Z
dc.date.available2023-08-02T14:16:50Z
dc.date.issued2016
dc.description.abstractHealth effects associated with occupational exposure to particulate matter have been studied by several authors. In this study were selected six industries of five different areas: Cork company 1, Cork company 2, poultry, slaughterhouse for cattle, riding arena and production of animal feed. The measurements tool was a portable device for direct reading. This tool provides information on the particle number concentration for six different diameters, namely 0.3 μm, 0.5 μm, 1 μm, 2.5 μm, 5 μm and 10 μm. The focus on these features is because they might be more closely related with adverse health effects. The aim is to identify the particles that better discriminate the industries, with the ultimate goal of classifying industries regarding potential negative effects on workers' health. Several methods of discriminant analysis were applied to data of occupational exposure to particulate matter and compared with respect to classification accuracy. The selected methods were linear discriminant analyses (LDA); linear quadratic discriminant analysis (QDA), robust linear discriminant analysis with selected estimators (MLE (Maximum Likelihood Estimators), MVE (Minimum Volume Elipsoid), "t", MCD (Minimum Covariance Determinant), MCD-A, MCD-B), multinomial logistic regression and artificial neural networks (ANN). The predictive accuracy of the methods was accessed through a simulation study. ANN yielded the highest rate of classification accuracy in the data set under study. Results indicate that the particle number concentration of diameter size 0.5 μm is the parameter that better discriminates industries.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationRamos, M. R., Carolino, E., Viegas, C., & Viegas, S. (2016). Comparison of discriminant analysis methods: Application to occupational exposure to particulate matter. AIP Conference Proceedings. https://doi.org/10.1063/1.4952236pt_PT
dc.identifier.doi10.1063/1.4952236pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.2/14717
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherAIP Publishingpt_PT
dc.subjectLinear discriminant analysispt_PT
dc.subjectRobust methodspt_PT
dc.subjectMultinomial logistic regressionpt_PT
dc.subjectArtificial neural networkspt_PT
dc.subjectOccupational exposurept_PT
dc.titleComparison of discriminant analysis methods: Application to occupational exposure to particulate matterpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceRhodes, Greecept_PT
oaire.citation.startPage470006pt_PT
oaire.citation.titleICNAAM 2015. AIP Conference Proceedings, International Conference of Numerical Analysis and Applied Mathematicspt_PT
oaire.citation.volume1738pt_PT
person.familyNameRamos
person.givenNameMaria do Rosário
person.identifier206757
person.identifier.ciencia-id3A1F-E648-078D
person.identifier.orcid0000-0001-9114-0807
person.identifier.ridP-4530-2015
person.identifier.scopus-author-id54403639500
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationc6cdb7b7-607d-4775-947f-d153ff6dded2
relation.isAuthorOfPublication.latestForDiscoveryc6cdb7b7-607d-4775-947f-d153ff6dded2

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
MRRamos 2016_Comparison of discriminant analysis (AIP Proceedings).pdf
Size:
596.68 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.97 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Matemática e Estatística | Comunicações em congressos, conferências e seminários / Communications in congresses, conferences