English(EN) Forecasting new power outages per county, hourly, 2 h ahead: 2.4× the PR-AUC of NWS warnings + SPC outlook on a held-out year [P]

AI模型提前2小时预测停电，准确率提高2.4倍

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-09 21:34

已开发出一个机器学习模型，能够以每小时为分辨率预测216个县的新停电情况，并提前两小时预测事件。该模型是XGBoost的实现，利用了HRRR预报中的风暴相关数据、县级特定信息以及当前的停电数据。它显著优于现有的国家气象局和SPC展望，在同等警报量下实现了2.4倍的PR-AUC和更高的精确度。 AI

影响该模型通过提供更准确、更及时的停电预测，可以改善灾害准备和公用事业响应。

排序理由该集群描述了机器学习在预测现实世界现象方面的新应用，并发布了论文和代码。 [lever_c_demoted from research: ic=1 ai=1.0]

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r/MachineLearning TIER_1 English(EN) · /u/CarRepresentative843 · 2026-11-09 21:34

预测各县未来2小时的停电情况，精确度是NWS预警+SPC展望的2.4倍（基于未公开的年度数据）[P]

<div class="md">Hi all! I built an hourly power outage forecast for 216 counties (MO + IL): P(≥5% of a county's customers newly out in the 6 h starting 2 h from now). Model: XGBoost on HRRR storm-related data (g…