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A systematic review of resilience strategies with emphasis on the role of machine learning and quantitative assessment under adverse operating conditions

delete2025-12-15
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OA
AI
K
Kamran Taghizad-Tavana *
A
Ashkan Safari
M
Mehrdad Tarafdar Hagh
A
Ali Esmaeel Nezhad
DOI:10.1016/j.ijepes.2025.111472delete
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Abstract

Abstract

En 中文
• Linking resilience concepts with simulations. • Elevating ML as core driver of resilience strategies. • Quantitative proof of mobile storage superiority. • Low-cost investments boosting resilience outcomes.
Keywords:
Resilience
Cyber-physical security
Smart distribution network
Machine learning
Flexible energy resources
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AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

I
International Journal of Electrical Power and Energy Systems
IF:
5
Papers:
1.1W
Citations:
3.1W

Organization

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Texas Tech University
Scholars:
7.0K
Papers: 5.8K
Citations: 1.5W
U
University of Tabriz
Scholars:
9.0K
Papers: 8.4K
Citations: 1.0W
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