Standard

Application of Long Short-Term Memory for Energy Load Prediction in the Microgrid Using Python Software. / Zhavoronkov, Alexander; Aksyonova, Olga; Aksyonova, Elena.
Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 94-99 (Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Harvard

Zhavoronkov, A, Aksyonova, O & Aksyonova, E 2021, Application of Long Short-Term Memory for Energy Load Prediction in the Microgrid Using Python Software. in Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021. Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 94-99, 2021 Ural-Siberian Smart Energy Conference, USSEC 2021, Новосибирск, Russian Federation, 13/11/2021. https://doi.org/10.1109/USSEC53120.2021.9655754

APA

Zhavoronkov, A., Aksyonova, O., & Aksyonova, E. (2021). Application of Long Short-Term Memory for Energy Load Prediction in the Microgrid Using Python Software. In Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021 (pp. 94-99). (Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/USSEC53120.2021.9655754

Vancouver

Zhavoronkov A, Aksyonova O, Aksyonova E. Application of Long Short-Term Memory for Energy Load Prediction in the Microgrid Using Python Software. In Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 94-99. (Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021). doi: 10.1109/USSEC53120.2021.9655754

Author

Zhavoronkov, Alexander ; Aksyonova, Olga ; Aksyonova, Elena. / Application of Long Short-Term Memory for Energy Load Prediction in the Microgrid Using Python Software. Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 94-99 (Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021).

BibTeX

@inproceedings{68b82ebb096040138267786e6ea27430,
title = "Application of Long Short-Term Memory for Energy Load Prediction in the Microgrid Using Python Software",
keywords = "load forecasting, long short-Term memory, machine learning, microgrid, Python, recurrent neural network",
author = "Alexander Zhavoronkov and Olga Aksyonova and Elena Aksyonova",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 Ural-Siberian Smart Energy Conference, USSEC 2021 ; Conference date: 13-11-2021 Through 15-11-2021",
year = "2021",
doi = "10.1109/USSEC53120.2021.9655754",
language = "English",
series = "Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "94--99",
booktitle = "Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021",
address = "United States",

}

RIS

TY - GEN

T1 - Application of Long Short-Term Memory for Energy Load Prediction in the Microgrid Using Python Software

AU - Zhavoronkov, Alexander

AU - Aksyonova, Olga

AU - Aksyonova, Elena

N1 - Publisher Copyright: © 2021 IEEE.

PY - 2021

Y1 - 2021

KW - load forecasting

KW - long short-Term memory

KW - machine learning

KW - microgrid

KW - Python

KW - recurrent neural network

UR - http://www.scopus.com/inward/record.url?scp=85124513643&partnerID=8YFLogxK

U2 - 10.1109/USSEC53120.2021.9655754

DO - 10.1109/USSEC53120.2021.9655754

M3 - Conference contribution

AN - SCOPUS:85124513643

T3 - Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021

SP - 94

EP - 99

BT - Proceedings of the 2021 Ural-Siberian Smart Energy Conference, USSEC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 Ural-Siberian Smart Energy Conference, USSEC 2021

Y2 - 13 November 2021 through 15 November 2021

ER -

ID: 29632960