Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/55489
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dc.contributor.authorMarco Velosoen_US
dc.contributor.authorPedro M. D'Oreyen_US
dc.contributor.authorSanti Phithakkitnukoonen_US
dc.contributor.authorCarlos Bentoen_US
dc.contributor.authorMichel Ferreiraen_US
dc.date.accessioned2018-09-05T02:57:09Z-
dc.date.available2018-09-05T02:57:09Z-
dc.date.issued2016-12-22en_US
dc.identifier.other2-s2.0-85010047787en_US
dc.identifier.other10.1109/ITSC.2016.7795874en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85010047787&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/55489-
dc.description.abstract© 2016 IEEE. In this work, we study exhaust gas concentration patterns in Porto, Portugal, and explore techniques to estimate the level of NO2 concentrations using taxi service and meteorological data as sensors. The exploratory analysis revealed daily and seasonal patterns of exhaust gases, with higher concentrations in the morning and on colder months. Based on nine months of data, we are able to estimate the concentration of NO2 using a multilayer perceptron (r = 0.7358) and linear regression (r = 0.5407). The analysis was extended to estimate NO and NOx, showing a lower performance.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleInferring Exhaust Gases Levels using Taxi Service and Meteorological Data: An Experiment in the City of Porto, Portugalen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSCen_US
article.stream.affiliationsUniversity of Coimbra, Centre for Informatics and Systemen_US
article.stream.affiliationsInstituto Politcnico de Coimbraen_US
article.stream.affiliationsUniversidade do Portoen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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