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2 April 2026

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Correction: Wu et al. From Forecasting to Foresight: Building an Autonomous O&M Brain for the New Power System Based on a Cognitive Digital Twin. Electronics 2025, 14, 4537

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1
Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518046, China
2
School of Mechano-Electronic Engineering, Xidian University, Xi’an 710126, China
3
School of Electronic Engineering, Xidian University, Xi’an 710126, China
4
School of Economics and Management, Xidian University, Xi’an 710126, China
The authors would like to make the following correction to their published paper [1]. The change is as follows:
References [11,55] in the original publication are incorrectly included and need to be replaced with the following references:
11.
Thwe, M.M.; Ştefanov, A.; Rajkumar, V.S.; Palensky, P. Digital Twins for Power Systems: Review of Current Practices, Requirements, Enabling Technologies, Data Federation, and Challenges. IEEE Access 2025, 13, 105517–105540.
55.
Malhotra, P.; Vig, L.; Shroff, G.; Agarwal, P. Long Short Term Memory Networks for Anomaly Detection in Time Series. In Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges, Belgium, 22–24 April 2015; pp. 89–94.
The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Wu, X.; Chen, Z.; Jiang, H.; Luo, S.; Zhao, Y.; Zhao, D.; Dang, P.; Gao, J.; Lin, L.; Wang, H. From Forecasting to Foresight: Building an Autonomous O&M Brain for the New Power System Based on a Cognitive Digital Twin. Electronics 2025, 14, 4537. [Google Scholar] [CrossRef] [Scilit]
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