A Genetic Programming Based Pollutant Concentration Predictor Design for Urban Pollution Monitoring Based on Multi-Sensor Electronic Nose

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dc.authorscopusid57207456092
dc.authorscopusid57221078940
dc.contributor.authorAri D.
dc.contributor.authorAlagoz B.B.
dc.date.accessioned2024-08-04T20:03:56Z
dc.date.available2024-08-04T20:03:56Z
dc.date.issued2021
dc.departmentİnönü Üniversitesien_US
dc.descriptionUmniah and UWalleten_US
dc.description2021 International Conference on Information Technology, ICIT 2021 -- 14 July 2021 through 15 July 2021 -- 170653en_US
dc.description.abstractAn important part of air pollution control is the pollution monitoring. Since industrial spectrometers are expensive equipment, the number of observation points to monitor air pollution over an urban area can be limited. The low-cost multi-sensors network can spread over areas and form a wide-area electronic nose to estimate pollutant concentration distributions. However, the collected multisensor data should be analyzed to correctly estimate pollutant concentrations. This study demonstrates implementation of genetic programming (GP) to obtain prediction models that can estimate CO and NO2 concentrations from multisensor electronic nose data. For this purpose, to function as an electronic nose, a regression model from a training data set is obtained by using a tree-based GP algorithm. In order to improve performance of the GP based prediction models, data normalization is performed and prediction performance enhancements are demonstrated via statistical performance analyses on a test data set. © 2021 IEEE.en_US
dc.identifier.doi10.1109/ICIT52682.2021.9491122
dc.identifier.endpage172en_US
dc.identifier.isbn9781665428705
dc.identifier.scopus2-s2.0-85112165495en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage168en_US
dc.identifier.urihttps://doi.org/10.1109/ICIT52682.2021.9491122
dc.identifier.urihttps://hdl.handle.net/11616/92218
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2021 International Conference on Information Technology, ICIT 2021 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectair qualityen_US
dc.subjectconcentration predictionen_US
dc.subjectelectronic noseen_US
dc.subjectGenetic programmingen_US
dc.subjectsensor data calibrationen_US
dc.titleA Genetic Programming Based Pollutant Concentration Predictor Design for Urban Pollution Monitoring Based on Multi-Sensor Electronic Noseen_US
dc.typeConference Objecten_US

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