Estimating co2 Emissions By Using Energy Intensıty Data of Oecd Countries

Simple item page
dc.contributor.authorGunduç, Semra
dc.contributor.authorEryiğit, Recep
dc.contributor.departmentBilgisayar Mühendisliğitr_TR
dc.contributor.facultyMühendislik Fakültesitr_TR
dc.date.accessioned2021-11-30T11:39:03Z
dc.date.available2021-11-30T11:39:03Z
dc.date.issued2019-06-30
dc.description.abstractIt is discussed that economic development has an essential effect on the country’s CO2 emission which plays an important role in global warming. In this research well-known machine learning algorithm Extreme Learning Machine, ELM, is used to investigate the relationship between CO2 emission and energy intensity for countries in OECD. The results indicate a strong correlation and the method perform well for estimation.tr_TR
dc.description.indexTrdizintr_TR
dc.identifier.endpage75tr_TR
dc.identifier.issn/e-issn2618-6462
dc.identifier.issue1tr_TR
dc.identifier.startpage68tr_TR
dc.identifier.urihttp://hdl.handle.net/20.500.12575/76518
dc.identifier.volume69tr_TR
dc.language.isoentr_TR
dc.publisherAnkara Üniversitesi Fen Fakültesitr_TR
dc.relation.journalCommunications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineeringtr_TR
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıtr_TR
dc.subjectExtreme Learning Machine (ELM)tr_TR
dc.subjectEnergy Intensitytr_TR
dc.subjectCO2 emissiontr_TR
dc.titleEstimating co2 Emissions By Using Energy Intensıty Data of Oecd Countriestr_TR
dc.typeArticletr_TR

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
46.pdf
Size:
895.46 KB
Format:
Adobe Portable Document Format
Description:
Dergi
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.62 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Cilt:61 Sayı:01 (2019)