Araştırma Makalesi

Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey

Cilt: 24 Sayı: 42 27 Haziran 2022
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Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey

Öz

One of the most important indicators of economic development is environmental quality. One of the most important sources of environmental pollution and climate change is greenhouse gas emissions. In this work, a new approach based on Gene Expression Programming (GEP) was used to forecast greenhouse gas (GHG) emissions depending on energy consumption, economic development (GDP), and population. The reliability of the GEP model was determined using several statistical indicators. In the relationship between energy consumption-GDP- population and GHG emissions, R2, MAPE, and RMSE values were found as 0.99337, 0.06987, and 7.1355, respectively. Sensitivity analysis seen that energy consumption have the highest effect on greenhouse gas emissions. The results obtained, it is showing that Gene Expression Programming can be successfully used to model greenhouse gas emissions.

Anahtar Kelimeler

Kaynakça

  1. Acheampong, A.O., and Boateng, E.B. (2019). Modelling Carbon Emission Intensity: Application Of Artificial Neural Network. Journal of Cleaner Production, 225, 833-856. http://dx.doi.org/10.1016/j.jclepro.2019.03.352 (2019).
  2. Ahmadi, M,H., Jashnani, H., Chau, K.W., Kumar, R., and Rosen, M.A. (2019). Carbon Dioxide Emissions Prediction Of Five Middle Eastern Countries Using Artificial Neural Networks. Energy Sources. Part A: Recovery. Utilization. and Environmental Effects, 1-13. http://dx.doi.org/10.1080/15567036.2019.1679914
  3. Amarante, J.C.A., Besarria, C.d.N., Souza, H.G.d., and dos Anjos Junior, O.R. (2021). The Relationship Between Economic Growth, Renewable and Nonrenewable Energy Use And CO2 Emissions: Empirical Evidences For Brazil. Greenhouse Gas Sci Technol., 11, 411–431. http://dx.doi.org/10.1002/ghg.2054
  4. Antanasijević, D., Pocajt, V., Ristić, M., and Perić-Grujić, A. (2015). Modeling Of Energy Consumption and Related GHG (Greenhouse Gas) Intensity and Emissions In Europe Using General Regression Neural Networks. Energy, 84, 816-824. http://dx.doi.org/10.1016/j.energy.2015.03.060
  5. Antanasijević, D.Z., Ristić M.Đ., Perić-Grujić, A.A., and Pocajt, V.V. (2014). Forecasting GHG Emissions Using an Optimized Artificial Neural Network Model Based on Correlation and Principal Component Analysis. International Journal of Greenhouse Gas Control, 20, 244-253. http://dx.doi.org/10.1016/j.ijggc.2013.11.011
  6. Ashrafi, K., Shafiepour, M., Ghasemi, L., and Araabi, B. (2012). Prediction Of Climate Change Induced Temperature Rise in Regional Scale Using Neural Network. International Journal of Environmental Research, 6(3), 677-688. https://ijer.ut.ac.ir/article_538_84bdd019d072d1cd9ea97d4dfe4ab49d.pdf
  7. Behrang, M.A., Assareh, E., Assari, M.R., and Ghanbarzadeh, A. (2011). Using Bees Algorithm and Artificial Neural Network to Forecast World Carbon Dioxide Emission. Energy Sources. Part A: Recovery. Utilization. and Environmental Effects, 33(19), 1747-1759. http://dx.doi.org/10.1080/15567036.2010.493920.
  8. Dong, K., Hochman, G., Zhang, Y., Sun, R., Li, H., and Liao, H. (2018). CO2 Emissions, Economic and Population Growth, And Renewable Energy: Empirical Evidence Across Regions. Energy Economics, 75, 180-192. http://dx.doi.org/10.1016/j.eneco.2018.08.017

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

27 Haziran 2022

Gönderilme Tarihi

26 Aralık 2021

Kabul Tarihi

27 Şubat 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: 24 Sayı: 42

Kaynak Göster

APA
Şencan, D., & Dikmen, E. (2022). Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi, 24(42), 81-96. https://izlik.org/JA54LU36PZ
AMA
1.Şencan D, Dikmen E. Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi. 2022;24(42):81-96. https://izlik.org/JA54LU36PZ
Chicago
Şencan, Derya, ve Erkan Dikmen. 2022. “Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey”. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi 24 (42): 81-96. https://izlik.org/JA54LU36PZ.
EndNote
Şencan D, Dikmen E (01 Haziran 2022) Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi 24 42 81–96.
IEEE
[1]D. Şencan ve E. Dikmen, “Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey”, Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi, c. 24, sy 42, ss. 81–96, Haz. 2022, [çevrimiçi]. Erişim adresi: https://izlik.org/JA54LU36PZ
ISNAD
Şencan, Derya - Dikmen, Erkan. “Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey”. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi 24/42 (01 Haziran 2022): 81-96. https://izlik.org/JA54LU36PZ.
JAMA
1.Şencan D, Dikmen E. Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi. 2022;24:81–96.
MLA
Şencan, Derya, ve Erkan Dikmen. “Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey”. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi, c. 24, sy 42, Haziran 2022, ss. 81-96, https://izlik.org/JA54LU36PZ.
Vancouver
1.Derya Şencan, Erkan Dikmen. Determination with Gene Expression Programming of the Relationship Between Socio-Economic Variables and Greenhouse Gas Emissions in Turkey. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi [Internet]. 01 Haziran 2022;24(42):81-96. Erişim adresi: https://izlik.org/JA54LU36PZ

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