Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini

Emre Aksoy; Nisa Ozge Onal Tugrul; Kamil Karacuha; Ibrahim Yazici; Omer Faruk Beyca

doi:10.1109/ELECO64362.2024.10847110

Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini

Emre Aksoy, Nisa Ozge Onal Tugrul, Kamil Karacuha, Ibrahim Yazici, Omer Faruk Beyca

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

Özet

Forecasting short-term electrical loads is crucial for power supply system management, sustainability and upkeep. There are two main objectives for this study. First, it seeks to provide a thorough comparison of deep learning and machine learning techniques while forecasting for 1-h-ahead and 1-d-ahead. To remove any disruptions from the time series and comprehend its dynamics, the study also concentrates on mathematically modelling electricity load data using fractional calculus.

Tercüme edilen katkı başlığı	Comparative Electrical Load Prediction with Machine Learning and Fractional Calculus Applications
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9798331518035
DOI'lar	https://doi.org/10.1109/ELECO64362.2024.10847110
Yayın durumu	Yayınlandı - 2024
Etkinlik	2024 Electrical, Electronics and Biomedical Engineering Conference at 15th National Conference on Electrical and Electronics Engineering, ELECO 2024 - Bursa, Turkey Süre: 28 Kas 2024 → 30 Kas 2024

Yayın serisi

Adı	Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2024 Electrical, Electronics and Biomedical Engineering Conference at 15th National Conference on Electrical and Electronics Engineering, ELECO 2024
Ülke/Bölge	Turkey
Şehir	Bursa
Periyot	28/11/24 → 30/11/24

Bibliyografik not

Publisher Copyright:
© 2024 IEEE.

Belgeye Erişim

10.1109/ELECO64362.2024.10847110

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Aksoy, E., Tugrul, N. O. O., Karacuha, K., Yazici, I., & Beyca, O. F. (2024). Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini. In Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings (Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ELECO64362.2024.10847110

Aksoy, Emre ; Tugrul, Nisa Ozge Onal ; Karacuha, Kamil et al. / Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini. Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2024. (Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings).

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title = "Makine {\"o}ǧrenmesi ve kesirli kalk{\"u}l{\"u}s uygulamalari ile kar{\c s}ila{\c s}tirmali elektrik y{\"u}k tahmini",

abstract = "Forecasting short-term electrical loads is crucial for power supply system management, sustainability and upkeep. There are two main objectives for this study. First, it seeks to provide a thorough comparison of deep learning and machine learning techniques while forecasting for 1-h-ahead and 1-d-ahead. To remove any disruptions from the time series and comprehend its dynamics, the study also concentrates on mathematically modelling electricity load data using fractional calculus.",

author = "Emre Aksoy and Tugrul, {Nisa Ozge Onal} and Kamil Karacuha and Ibrahim Yazici and Beyca, {Omer Faruk}",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 Electrical, Electronics and Biomedical Engineering Conference at 15th National Conference on Electrical and Electronics Engineering, ELECO 2024 ; Conference date: 28-11-2024 Through 30-11-2024",

year = "2024",

doi = "10.1109/ELECO64362.2024.10847110",

language = "T{\"u}rk{\c c}e",

series = "Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings",

address = "United States",

}

Aksoy, E, Tugrul, NOO , Karacuha, K, Yazici, I & Beyca, OF 2024, Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini. in Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings. Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2024 Electrical, Electronics and Biomedical Engineering Conference at 15th National Conference on Electrical and Electronics Engineering, ELECO 2024, Bursa, Turkey, 28/11/24. https://doi.org/10.1109/ELECO64362.2024.10847110

Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini. / Aksoy, Emre; Tugrul, Nisa Ozge Onal ; Karacuha, Kamil et al.
Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2024. (Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini

AU - Aksoy, Emre

AU - Tugrul, Nisa Ozge Onal

AU - Karacuha, Kamil

AU - Yazici, Ibrahim

AU - Beyca, Omer Faruk

PY - 2024

Y1 - 2024

N2 - Forecasting short-term electrical loads is crucial for power supply system management, sustainability and upkeep. There are two main objectives for this study. First, it seeks to provide a thorough comparison of deep learning and machine learning techniques while forecasting for 1-h-ahead and 1-d-ahead. To remove any disruptions from the time series and comprehend its dynamics, the study also concentrates on mathematically modelling electricity load data using fractional calculus.

AB - Forecasting short-term electrical loads is crucial for power supply system management, sustainability and upkeep. There are two main objectives for this study. First, it seeks to provide a thorough comparison of deep learning and machine learning techniques while forecasting for 1-h-ahead and 1-d-ahead. To remove any disruptions from the time series and comprehend its dynamics, the study also concentrates on mathematically modelling electricity load data using fractional calculus.

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U2 - 10.1109/ELECO64362.2024.10847110

DO - 10.1109/ELECO64362.2024.10847110

M3 - Konferans katkısı

AN - SCOPUS:85217841977

T3 - Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings

BT - Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2024 Electrical, Electronics and Biomedical Engineering Conference at 15th National Conference on Electrical and Electronics Engineering, ELECO 2024

Y2 - 28 November 2024 through 30 November 2024

ER -

Aksoy E, Tugrul NOO , Karacuha K, Yazici I, Beyca OF. Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini. In Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2024. (Electrical-Electronics and Biomedical Engineering Conference, ELECO 2024 - Proceedings). doi: 10.1109/ELECO64362.2024.10847110

Makine öǧrenmesi ve kesirli kalkülüs uygulamalari ile karşilaştirmali elektrik yük tahmini

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap