Predicting Power Outages with AI
Published:Dec 27, 2025 20:30
•1 min read
•ArXiv
Analysis
This paper addresses a critical real-world problem: predicting power outages during extreme events. The integration of diverse data sources (weather, socio-economic, infrastructure) and the use of machine learning models, particularly LSTM, is a significant contribution. Understanding community vulnerability and the impact of infrastructure development on outage risk is crucial for effective disaster preparedness and resource allocation. The focus on low-probability, high-consequence events makes this research particularly valuable.
Key Takeaways
- •Predictive models can be built to forecast power outages during extreme events.
- •Integrating weather, socio-economic, and infrastructure data improves prediction accuracy.
- •LSTM networks show promise in predicting power outages.
- •Stronger economic conditions and developed infrastructure are associated with lower outage occurrence.
Reference
“The LSTM network achieves the lowest prediction error.”