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

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dc.authoridNursaç Kurt / 0000-0002-9338-0174
dc.authorscopusidNursaç Kurt / 57419177700
dc.authorwosidNursaç Kurt / CZH-1635-2022
dc.contributor.authorKurt, Nursaç
dc.contributor.authorOzturk, O.
dc.contributor.authorBeken, M.
dc.date.accessioned2022-01-28T14:16:42Z
dc.date.available2022-01-28T14:16:42Z
dc.date.issued2021en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri 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. © 2021 IEEE.en_US
dc.identifier.citationKurt, N., Ozturk, O., & Beken, M. (2021). Estimation of gas emission values on highways in turkey with machine learning. Paper presented at the 10th IEEE International Conference on Renewable Energy Research and Applications, ICRERA 2021, 443-446. doi:10.1109/ICRERA52334.2021.9598769en_US
dc.identifier.doi10.1109/ICRERA52334.2021.9598769en_US
dc.identifier.endpage446en_US
dc.identifier.scopus2-s2.0-85123193397en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage443en_US
dc.identifier.urihttps://doi.org/10.1109/ICRERA52334.2021.9598769
dc.identifier.urihttps://hdl.handle.net/20.500.12713/2440
dc.identifier.wosWOS:000761616700076en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorKurt, Nursaç
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof10th IEEE International Conference on Renewable Energy Research and Applicationsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGas Emissionsen_US
dc.subjectMachine Learningen_US
dc.subjectRegression Analysisen_US
dc.subjectRoaden_US
dc.subjectTransporten_US
dc.titleEstimation of gas emission values on highways in Turkey with machine learningen_US
dc.typeConference Objecten_US

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