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dc.contributor.authorHolmes, Geoffrey
dc.contributor.authorFletcher, Dale
dc.contributor.authorReutemann, Peter
dc.coverage.spatialConference held at Ottawa, Canadaen_NZ
dc.date.accessioned2010-08-19T22:00:31Z
dc.date.available2010-08-19T22:00:31Z
dc.date.issued2010
dc.identifier.citationHolmes, G., Fletcher, D. & Reutemann, P. (2010). Predicting polycyclic aromatic hydrocarbon concentrations in soil and water samples. In D.A. Swayne, W. Yang, A.A. Voinov, A. Rizzoli & T. Filatova (Eds.), Proceedings of International Environmental Modelling and Software Society (iEMSs) 2010 International Congress on Environmental Modelling and Software Modelling for Environment’s Sake, Fifth Biennial Meeting, July 5-8 2010, Ottawa, Canada.en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/4374
dc.description.abstractPolycyclic Aromatic Hydrocarbons (PAHs) are compounds found in the environment that can be harmful to humans. They are typically formed due to incomplete combustion and as such remain after burning coal, oil, petrol, diesel, wood, household waste and so forth. Testing laboratories routinely screen soil and water samples taken from potentially contaminated sites for PAHs using Gas Chromatography Mass Spectrometry (GC-MS). A GC-MS device produces a chromatogram which is processed by an analyst to determine the concentrations of PAH compounds of interest. In this paper we investigate the application of data mining techniques to PAH chromatograms in order to provide reliable prediction of compound concentrations. A workflow engine with an easy-to-use graphical user interface is at the heart of processing the data. This engine allows a domain expert to set up workflows that can load the data, preprocess it in parallel in various ways and convert it into data suitable for data mining toolkits. The generated output can then be evaluated using different data mining techniques, to determine the impact of preprocessing steps on the performance of the generated models and for picking the best approach. Encouraging results for predicting PAH compound concentrations, in terms of correlation coefficients and root-mean-squared error are demonstrated.en_NZ
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherInternational Environmental Modelling and Software Societyen_NZ
dc.relation.urihttp://www.iemss.org/iemss2010/proceedings.htmlen_NZ
dc.rightsThis article has been published in Proceedings of International Environmental Modelling and Software Society (iEMSs) 2010 International Congress on Environmental Modelling and Software Modelling for Environment’s Sake, Fifth Biennial Meeting, July 5-8 2010, Ottawa, Canada. Used with permission.en_NZ
dc.sourceiEMSs 2010en_NZ
dc.subjectcomputer scienceen_NZ
dc.subjectGC-MSen_NZ
dc.subjectdata miningen_NZ
dc.subjectPAHen_NZ
dc.subjectworkflowsen_NZ
dc.titlePredicting polycyclic aromatic hydrocarbon concentrations in soil and water samplesen_NZ
dc.typeConference Contributionen_NZ
dc.relation.isPartOfModelling for Environment's Sake: Proceedings of the 5th Biennial Conference of the International Environmental Modelling and Software Societyen_NZ
pubs.begin-page1812en_NZ
pubs.elements-id19656
pubs.end-page1819en_NZ
pubs.finish-date2010-07-08en_NZ
pubs.place-of-publicationCanadaen_NZ
pubs.start-date2010-07-05en_NZ
pubs.volume3en_NZ


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