Araştırma Makalesi
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Yıl 2022, Cilt 1, Sayı 1, 9 - 15, 30.06.2022

Öz

Kaynakça

  • Bashawyah, D. A., & Qaisar, S. M. (2021). Machine Learning Based Short-Term Load Forecasting for Smart Meter Energy Consumption Data in London Households, 99–102. https://doi.org/10.1109/elit53502.2021.9501104
  • Chicco, D., Warrens, M. J., & Jurman, G. (2021). No Title. PeerJ Computer Science, 5. EPIAS. (n.d.). EPIAS. Retrieved February 1, 2022, from https://seffaflik.epias.com.tr/transparency/tuketim/tuketici-bilgisi/tuketim-miktarlari.xhtml
  • Fayaz, M. (n.d.). Prediction of Energy Consumption in the Buildings Using Multi-Layer Perceptron and Random Forest. International Journal of Advanced Science and Technology, 101, 13–22.
  • González-Briones, A., Hernandez, G., Corchado, J. M., Omatu, S., & Mohamad, M. S. (2019). Machine Learning Models for Electricity Consumption Forecasting: A Review. 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019. https://doi.org/10.1109/CAIS.2019.8769508
  • Nallathambi, S., & Ramasamy, K. (2017). Prediction of electricity consumption based on DT and RF: An application on USA country power consumption. Proceedings - 2017 IEEE International Conference on Electrical, Instrumentation and Communication Engineering, ICEICE 2017, 2017-Decem(1), 1–7. https://doi.org/10.1109/ICEICE.2017.8191939
  • Qu, Z., Liu, H., Wang, Z., Xu, J., Zhang, P., & Zeng, H. (2021). Energy & Buildings A combined genetic optimization with AdaBoost ensemble model for anomaly detection in buildings electricity consumption. Energy & Buildings, 248, 111193. https://doi.org/10.1016/j.enbuild.2021.111193
  • Sarker, I. H. (2021). Machine Learning: Algorithms, Real-World Applications and Research Directions. SN Computer Science, 2(3), 160. https://doi.org/10.1007/s42979-021-00592-x
  • Shaikh, A., & Namdeo, V. (2021). Unerstanding Machine Learning Approach on Various Algorithms: A Case Study Implementation. 2021 6th International Conference for Convergence in Technology, I2CT 2021, 2–6. https://doi.org/10.1109/I2CT51068.2021.9418166

Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey

Yıl 2022, Cilt 1, Sayı 1, 9 - 15, 30.06.2022

Öz

The COVID-19 pandemic associated with the lockdown measures caused an extraordinary impact on the economies of all countries in the world. Under lockdown, dramatic reductions in industry and services resulted in electricity demand dropping to Sunday levels, though higher domestic use yielded a relatively small partial offset. In this study, we analyzed overall electricity consumption in Turkey starting from pre-COVID days until now to illustrate the pandemic's effects on consumption. For this purpose, we built an ensemble machine learning model for the analysis. Findings revealed that the proposed boosting (AdaBoost) ensemble algorithm (RMSE: 41848.7, MAE: 18574.3, R2 :0.89) is a significant contributory factor in the analysis of data related to electricity consumption. Results also show that boosting (AdaBoost) ensemble learning algorithm is more preferable in the use of energy-related data than the bagging (random forest) and single-based algorithms (deep neural networks).

Kaynakça

  • Bashawyah, D. A., & Qaisar, S. M. (2021). Machine Learning Based Short-Term Load Forecasting for Smart Meter Energy Consumption Data in London Households, 99–102. https://doi.org/10.1109/elit53502.2021.9501104
  • Chicco, D., Warrens, M. J., & Jurman, G. (2021). No Title. PeerJ Computer Science, 5. EPIAS. (n.d.). EPIAS. Retrieved February 1, 2022, from https://seffaflik.epias.com.tr/transparency/tuketim/tuketici-bilgisi/tuketim-miktarlari.xhtml
  • Fayaz, M. (n.d.). Prediction of Energy Consumption in the Buildings Using Multi-Layer Perceptron and Random Forest. International Journal of Advanced Science and Technology, 101, 13–22.
  • González-Briones, A., Hernandez, G., Corchado, J. M., Omatu, S., & Mohamad, M. S. (2019). Machine Learning Models for Electricity Consumption Forecasting: A Review. 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019. https://doi.org/10.1109/CAIS.2019.8769508
  • Nallathambi, S., & Ramasamy, K. (2017). Prediction of electricity consumption based on DT and RF: An application on USA country power consumption. Proceedings - 2017 IEEE International Conference on Electrical, Instrumentation and Communication Engineering, ICEICE 2017, 2017-Decem(1), 1–7. https://doi.org/10.1109/ICEICE.2017.8191939
  • Qu, Z., Liu, H., Wang, Z., Xu, J., Zhang, P., & Zeng, H. (2021). Energy & Buildings A combined genetic optimization with AdaBoost ensemble model for anomaly detection in buildings electricity consumption. Energy & Buildings, 248, 111193. https://doi.org/10.1016/j.enbuild.2021.111193
  • Sarker, I. H. (2021). Machine Learning: Algorithms, Real-World Applications and Research Directions. SN Computer Science, 2(3), 160. https://doi.org/10.1007/s42979-021-00592-x
  • Shaikh, A., & Namdeo, V. (2021). Unerstanding Machine Learning Approach on Various Algorithms: A Case Study Implementation. 2021 6th International Conference for Convergence in Technology, I2CT 2021, 2–6. https://doi.org/10.1109/I2CT51068.2021.9418166

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Research Articles
Yazarlar

Selim BUYRUKOĞLU>
CANKIRI KARATEKIN UNIVERSITY
0000-0001-7844-3168
Türkiye


Ayhan AKBAŞ> (Sorumlu Yazar)
ABDULLAH GÜL ÜNİVERSİTESİ
0000-0002-6425-104X
Türkiye

Erken Görünüm Tarihi 30 Haziran 2022
Yayımlanma Tarihi 30 Haziran 2022
Başvuru Tarihi 16 Mart 2022
Kabul Tarihi 25 Mayıs 2022
Yayınlandığı Sayı Yıl 2022, Cilt 1, Sayı 1

Kaynak Göster

Bibtex @araştırma makalesi { inotech1088633, journal = {Inspiring Technologies and Innovations}, address = {Kuzeykent Mahallesi Org. Atilla ATEŞ Paşa Caddesi Kastamonu Üniversitesi Mühendislik ve Mimarlık Fakültesi PK: 37150 Merkez/KASTAMONU}, publisher = {Kastamonu Üniversitesi}, year = {2022}, volume = {1}, number = {1}, pages = {9 - 15}, title = {Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey}, key = {cite}, author = {Akbaş, Ayhan} }
APA Buyrukoğlu, S. & Akbaş, A. (2022). Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey . Inspiring Technologies and Innovations , 1 (1) , 9-15 . Retrieved from https://dergipark.org.tr/tr/pub/inotech/issue/70702/1088633
MLA Buyrukoğlu, S. , Akbaş, A. "Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey" . Inspiring Technologies and Innovations 1 (2022 ): 9-15 <https://dergipark.org.tr/tr/pub/inotech/issue/70702/1088633>
Chicago Buyrukoğlu, S. , Akbaş, A. "Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey". Inspiring Technologies and Innovations 1 (2022 ): 9-15
RIS TY - JOUR T1 - Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey AU - SelimBuyrukoğlu, AyhanAkbaş Y1 - 2022 PY - 2022 N1 - DO - T2 - Inspiring Technologies and Innovations JF - Journal JO - JOR SP - 9 EP - 15 VL - 1 IS - 1 SN - - M3 - UR - Y2 - 2022 ER -
EndNote %0 Inspiring Technologies and Innovations Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey %A Selim Buyrukoğlu , Ayhan Akbaş %T Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey %D 2022 %J Inspiring Technologies and Innovations %P - %V 1 %N 1 %R %U
ISNAD Buyrukoğlu, Selim , Akbaş, Ayhan . "Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey". Inspiring Technologies and Innovations 1 / 1 (Haziran 2022): 9-15 .
AMA Buyrukoğlu S. , Akbaş A. Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey. INOTECH. 2022; 1(1): 9-15.
Vancouver Buyrukoğlu S. , Akbaş A. Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey. Inspiring Technologies and Innovations. 2022; 1(1): 9-15.
IEEE S. Buyrukoğlu ve A. Akbaş , "Efficiency of Ensemble Learning Algorithms in the Analysis of Effects of Covid-19 Pandemic on Electricity Consumption in Turkey", Inspiring Technologies and Innovations, c. 1, sayı. 1, ss. 9-15, Haz. 2022