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» Predicting Electricity Distribution Feeder Failures Using Ma...
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AAAI
2006
13 years 6 months ago
Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis
A Machine Learning (ML) System known as ROAMS (Ranker for Open-Auto Maintenance Scheduling) was developed to create failure-susceptibility rankings for almost one thousand 13.8kV-...
Philip Gross, Albert Boulanger, Marta Arias, David...
ICMLA
2009
13 years 2 months ago
Ranking Electrical Feeders of the New York Power Grid
components of a system by susceptibility to failure. In this extended abstract, we present an ongoing project to rank the underground primary feeders of Consolidated Edison Company...
Philip Gross, Ansaf Salleb-Aouissi, Haimonti Dutta...
ICMLA
2009
13 years 2 months ago
Alive on Back-feed Culprit Identification via Machine Learning
We describe an application of machine learning techniques toward the problem of predicting which network protector switch is the cause of an Alive on Back-Feed (ABF) event in the ...
Bert C. Huang, Ansaf Salleb-Aouissi, Philip Gross