Estimating Smart Grid Stability with Hybrid RNN+LSTM Deep Learning Approach-Reference-Cited by-同舟云学术

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Estimating Smart Grid Stability with Hybrid RNN+LSTM Deep Learning Approach

Published:2024-05-27 Issue: Volume: Page:738-741
ISSN:
Container-title:2024 12th International Conference on Smart Grid (icSmartGrid)
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Author:

Oyucu Saadin¹,Sağıroğlu Şeref²,Aksöz Ahmet³,Biçer Emre⁴

Affiliation:

1. Faculty of Engineering,Department of Computer Engineering,Adıyaman,Türkiye

2. Gazi University, Artificial Intelligence and Big Data Analytics Security R&D Center,Ankara,Türkiye

3. Sivas Cumhuriyet University,Mobilers Team,Sivas,Türkiye

4. Sivas University of Science and Technology,Faculty of Engineering and Natural Sciences, Battery Research Laboratory,Sivas,Türkiye

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10577998/10578066/10578179.pdf?arnumber=10578179

Reference11 articles.

1. A Review on Digital Twin Technology in Smart Grid, Transportation System and Smart City: Challenges and Future

2. Classification of smart grid stability prediction using cascade machine learning methods and the internet of things in smart grid

3. Analysis and prediction of the penetration of renewable energy in power systems using artificial neural network

4. A novel approach to predicting the stability of the smart grid utilizing MLP-ELM technique

5. Revitalizing the Electric Grid: A Machine Learning Paradigm for Ensuring Stability in the U.S.A

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