Predicting electricity distribution feeder failures using machine learning susceptibility analysis

Proceedings of the National Conference on Artificial Intelligence

Volumn 2, Issue , 2006, Pages 1705-1711

  Gross, Philip ^a   Boulanger, Albert ^a   Arias, Marta ^a   Waltz, David ^a   Long, Philip M ^a,c   Lawson, Charles ^a,d   Anderson, Roger ^a   Koenig, Matthew ^b   Mastrocinque, Mark ^b   Fairechio, William ^b   Johnson, John A ^b   Lee, Serena ^b   Doherty, Frank ^b   Kressner, Arthur ^b  

^a Howard Hughes Medical Institute   (United States)

^b Operations Analysis Group   (United States)

^c GOOGLE INC   (United States)

^d Digimedia Corp   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENERGY DISTRIBUTION; FAILURE SUSCEPTIBILITY; FEEDER FAILURES; FEEDER SYSTEM;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CURRENT LIMITING REACTORS; ELECTRIC UTILITIES;

LEARNING SYSTEMS;

EID: 33750704249     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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