ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES
Yıl: 2019 Cilt: 61 Sayı: 1 Sayfa Aralığı: 68 - 75 Metin Dili: İngilizce DOI: 10.33769/aupse.525368 İndeks Tarihi: 16-11-2020
ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES
Öz: It is discussed that economic development has an essential effect onthe country’s CO2 emission which plays an important role in global warming. Inthis research well-known machine learning algorithm Extreme Learning Machine,ELM, is used to investigate the relationship between CO2 emission and energyintensity for countries in OECD. The results indicate a strong correlation and themethod perform well for estimation.
Anahtar Kelime: Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
- [1] I. Ozturk and A. Caravci, CO2 emissions, energy consumption and economic growth in Turkey. Renew Sustain Energy Rev 2010;14:3220–5.
- [2] BP. BP statistical review of world energy June 2016; 2016. http://www.bp.com/ statisticalreview.
- [3] SJ. Davis, K. Caldeira and HD. Matthews, Future CO2 emissions and climate change from existing energy infrastructure. Science 2010;329:1330–3.
- [4] P.R. Ehrlich and J.P. Holdren, Impact of population growth. Science 1971, 3977, 1212–1217.
- [5] A. Shi, The impact of population pressure on global carbon dioxide emissions, 1975– 1996: Evidence from pooled cross-country data. Ecol. Econ. 2003, 1, 29–42.
- [6] M. Wang and C. Feng, Decomposition of energy-related CO2 emissions in China: an empirical analysis based on provincial panel data of three sectors. Appl Energy 2017;190:772–87.
- [7] B. Lin and H. Liu, CO2 emissions of China’s commercial and residential buildings: Evidence and reduction policy. Build Environ 2015;92:418–31.
- [8] www.worlddatabank.com
- [9] J. Long, L. Shuai, H. Bin and L. Mei, A survey on projection neural networks and their applications Applied Soft Computing, Volume 76, 2019, Pages 533-544
- [10] G.B. Huang, Q.Y. Zhu and C.K. Siew, Extreme learning machine:Theory and applications, Neurocomputing 70 (2006a) 489501
- [11] S. Gang and D. Qun, A novel double deep ELMs ensemble system for time series forecasting , Knowledge-Based Systems, Volume 134, 2017, Pages 31-49.
- [12] K. Marius, Y. Yang, L. Caihong, C. Yanhua and L. Lian Mixed kernel based extreme learning machine for electric load forecasting Neurocomputing, Volume 312, 2018, Pages 90-106.
| APA | Eryigit R, gunduc s (2019). ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. , 68 - 75. 10.33769/aupse.525368 |
| Chicago | Eryigit Recep,gunduc semra ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. (2019): 68 - 75. 10.33769/aupse.525368 |
| MLA | Eryigit Recep,gunduc semra ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. , 2019, ss.68 - 75. 10.33769/aupse.525368 |
| AMA | Eryigit R,gunduc s ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. . 2019; 68 - 75. 10.33769/aupse.525368 |
| Vancouver | Eryigit R,gunduc s ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. . 2019; 68 - 75. 10.33769/aupse.525368 |
| IEEE | Eryigit R,gunduc s "ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES." , ss.68 - 75, 2019. 10.33769/aupse.525368 |
| ISNAD | Eryigit, Recep - gunduc, semra. "ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES". (2019), 68-75. https://doi.org/10.33769/aupse.525368 |
| APA | Eryigit R, gunduc s (2019). ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. Communications Faculty of Sciences University of Ankara Series A2-A3: Physical Sciences and Engineering, 61(1), 68 - 75. 10.33769/aupse.525368 |
| Chicago | Eryigit Recep,gunduc semra ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. Communications Faculty of Sciences University of Ankara Series A2-A3: Physical Sciences and Engineering 61, no.1 (2019): 68 - 75. 10.33769/aupse.525368 |
| MLA | Eryigit Recep,gunduc semra ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. Communications Faculty of Sciences University of Ankara Series A2-A3: Physical Sciences and Engineering, vol.61, no.1, 2019, ss.68 - 75. 10.33769/aupse.525368 |
| AMA | Eryigit R,gunduc s ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. Communications Faculty of Sciences University of Ankara Series A2-A3: Physical Sciences and Engineering. 2019; 61(1): 68 - 75. 10.33769/aupse.525368 |
| Vancouver | Eryigit R,gunduc s ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES. Communications Faculty of Sciences University of Ankara Series A2-A3: Physical Sciences and Engineering. 2019; 61(1): 68 - 75. 10.33769/aupse.525368 |
| IEEE | Eryigit R,gunduc s "ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES." Communications Faculty of Sciences University of Ankara Series A2-A3: Physical Sciences and Engineering, 61, ss.68 - 75, 2019. 10.33769/aupse.525368 |
| ISNAD | Eryigit, Recep - gunduc, semra. "ESTIMATING CO2 EMISSIONS BY USING ENERGY INTENSITY DATA OF OECD COUNTRIES". Communications Faculty of Sciences University of Ankara Series A2-A3: Physical Sciences and Engineering 61/1 (2019), 68-75. https://doi.org/10.33769/aupse.525368 |
