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X-ORIGINAL-URL:https://utilityanalytics.com/
X-WR-CALNAME:Utility Analytics Institute
X-WR-CALDESC:Utility led community for analytics professionals
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BEGIN:VEVENT
CLASS:PUBLIC
UID:MEC-e420ab190f1f9223de3684d74b53be0a@utilityanalytics.com
DTSTART:20250924T190000Z
DTEND:20250924T200000Z
DTSTAMP:20250823T165700Z
CREATED:20250823
LAST-MODIFIED:20250909
PRIORITY:5
SEQUENCE:12
TRANSP:OPAQUE
SUMMARY:September 24 Asset Health Analytics Community – Using Machine Learning to Predict Hot Sockets Before They Occur
DESCRIPTION:Join the Asset Health Analytics Community on Wednesday, September 24, 2025 at 2:00 PM CT for a presentation with Q&A/open discussion on, “Using Machine Learning to Predict Hot Sockets Before They Occur” led by Alex Kizhner, Data Scientist, Metering Analytics, Enterprise Analytics & Automation at Ameren.\n\nSession Description:\nDuring this session Ameren will discuss a predictive model that was built to identify electric meters at risk of developing hot sockets, either environmental or mechanical, before triggering a Temperature Threshold Exceeded Event (TTEE). This enables targeted field interventions during normal business hours, reducing emergency truck rolls, improving safety, and optimizing operational efficiency.\n \n*UAI Utility Members can register and access all nine of our Analytics Communities via our Community Page ( https://utilityanalytics.com/communities/ ). Not a part of the Asset Health Community and want to join this session? Please use our direct link here to request access. You will find the Teams meeting credentials to the upcoming meeting at the top of the feed on this page. If you have any questions or run into any issues, please contact us at info@utilityanalytics.com ( mailto:info@utilityanalytics.com ).\n
URL:https://utilityanalytics.com/events/using-machine-learning-to-predict-hot-sockets-before-they-occur/
CATEGORIES:Community Meeting
LOCATION:Virtual
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