Estimation of gas emission values on highways in Turkey with machine learning

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dc.authorid0000-0003-2989-3781en_US
dc.authorid0000-0002-9338-0174en_US
dc.contributor.authorKurt, Nursaç
dc.contributor.authorÖztürk, Oktay
dc.contributor.authorBeken, Murat
dc.date.accessioned2023-06-08T08:20:41Z
dc.date.available2023-06-08T08:20:41Z
dc.date.issued2021en_US
dc.departmentBAİBÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractDue to its geographical location, Turkey has been home to many civilizations for centuries. It has always acted as a bridge between west and east and will continue to do so. The development of road networks in Turkey and the difference in transportation methods are increasing the number of national and international traveling vehicles day by day. In this study, gas emission (CO2, CH4, N2O) value changes have been predicted according to vehicle types of vehicle mobility on highways using machine learning (Linear Regression, Bayesian Ridge, Random Forest Regressor, MLP Regressor, SVR) algorithms. Based on these results, the gas emission value and environmental impact that may occur in the future are estimated-each method evaluated with MAE, MSE, RMSE, and R2 statistical metrics. As a result, we obtain R square scores of 0.963231 for CO2, 0.9856 for CH4, and 0.982404 for N2O from the random forest regressor, random forest regressor, and MLP regressor, respectively.en_US
dc.identifier.citationN. Kurt, O. Ozturk and M. Beken, "Estimation of Gas Emission Values on Highways in Turkey with Machine Learning," 2021 10th International Conference on Renewable Energy Research and Application (ICRERA), Istanbul, Turkey, 2021, pp. 443-446, doi: 10.1109/ICRERA52334.2021.9598769.en_US
dc.identifier.doi10.1109/ICRERA52334.2021.9598769
dc.identifier.endpage446en_US
dc.identifier.isbn978-1-6654-4524-5
dc.identifier.issn2377-6897
dc.identifier.scopus2-s2.0-85123193397en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage443en_US
dc.identifier.urihttp://dx.doi.org/10.1109/ICRERA52334.2021.9598769
dc.identifier.urihttps://hdl.handle.net/20.500.12491/11078
dc.identifier.wosWOS:000761616700076en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorBeken, Murat
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof10th IEEE International Conference on Renewable Energy Research and Applications (ICRERA 2021)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRoaden_US
dc.subjectTransporten_US
dc.subjectMachine Learningen_US
dc.subjectRegression Analysisen_US
dc.subjectGas Emissionsen_US
dc.titleEstimation of gas emission values on highways in Turkey with machine learningen_US
dc.typeConference Objecten_US

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