Evaluating Large Language Models for Forced Outage Risk Prediction: Benefits and Comparison to Machine Learning
This story is from 2026-09-07. It is preserved in the archive; the latest stories are on the live feed.
arXiv:2609.04272v1 Announce Type: new Abstract: This study examines the ability of large language models (LLMs) to predict the risk of weather-related forced outages in the distribution grid in a zero-shot framework, without labeled training data. The problem is formulated as a binary severity clas…
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- 2026-09-07 04:00 · arXiv cs.LG
Evaluating Large Language Models for Forced Outage Risk Prediction: Benefits and Comparison to Machine Learning
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