ML Anthology

Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis

Philip Gross, Albert Boulanger, Marta Arias, David L. Waltz, Philip M. Long, Charles Lawson, Roger Anderson, Matthew Koenig, Mark Mastrocinque, William Fairechio, John A. Johnson, Serena Lee, Frank Doherty, Arthur Kressner
AAAI 2006 pp. 1705-1711
/aaai/2006/gross2006aaai-predicting/

Abstract

This work has been partly supported by a research contract from Consolidated Edison. 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-27kV energy distribution feeder cables that supply electricity to the boroughs of New

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Cite

Text

Gross et al. "Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis." AAAI Conference on Artificial Intelligence, 2006.

Markdown

[Gross et al. "Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis." AAAI Conference on Artificial Intelligence, 2006.](https://mlanthology.org/aaai/2006/gross2006aaai-predicting/)

BibTeX

@inproceedings{gross2006aaai-predicting,
  title     = {{Predicting Electricity Distribution Feeder Failures Using Machine Learning Susceptibility Analysis}},
  author    = {Gross, Philip and Boulanger, Albert and Arias, Marta and Waltz, David L. and Long, Philip M. and Lawson, Charles and Anderson, Roger and Koenig, Matthew and Mastrocinque, Mark and Fairechio, William and Johnson, John A. and Lee, Serena and Doherty, Frank and Kressner, Arthur},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2006},
  pages     = {1705-1711},
  url       = {https://mlanthology.org/aaai/2006/gross2006aaai-predicting/}
}