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September 23, 2025EnergiesOpen Access

Power Outage Prediction on Overhead Power Lines on the Basis of Their Technical Parameters: Machine Learning Approach

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Authors

VBVadim BolshevDBDmitry BudnikovADAndrei Dzeikalo

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Overview

This study demonstrates the effectiveness of machine learning for predicting power outages, indicating Logistic Regression is the most accurate classifier used.

Key Points

  • The research shows that power line parameters can effectively predict power outages.
  • Logistic Regression achieved the highest quality metrics for outage prediction with ROC AUC of 0.78.
  • Machine learning classifiers, including Support Vector Machine and Random Forest, were evaluated for predicting outages.
  • Feature importance analysis provided insights into the impact of power line parameters on failure probability.

Cite This Study

Bolshev et al. (2025) studied this question.

synapsesocial.com/papers/68d43eeb713b0b5dfea7ee2dhttps://doi.org/10.3390/en18185034
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