In this work, Extreme Learning Machine (ELM) algorithm is used to estimate the GDP per capita. The amount of electricity production, from four different sources, is chosen as input parameters. To find out the most relevant input data for a reasonable estimation of GDP, different sources introduced separately to ELM. By following the coefficient of determination of estimation, by trial and error, results are obtained. The residuals are also given to show that model perform well. Renewable energy sources produce the best results in the estimation of GDP.
Gross domestic product estimation extreme learning machine electricity production sources
Birincil Dil | İngilizce |
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Konular | Mühendislik |
Bölüm | Research Article |
Yazarlar | |
Yayımlanma Tarihi | 30 Haziran 2021 |
Gönderilme Tarihi | 11 Şubat 2019 |
Kabul Tarihi | 3 Şubat 2021 |
Yayımlandığı Sayı | Yıl 2021 Cilt: 63 Sayı: 1 |
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.