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Abstract—Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance.
May 19, 2011 · Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance.
Machine Learning for the New York City Power Grid. February 2012. Read at the source: Machine Learning for the New York City Power Grid. MITEI Author. Energy ...
A general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems is ...
We introduce a general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems.
The goal is to predict electrical failures, including manhole fires and explosions in New York City and the data mining process behind it.
The document discusses using machine learning to help maintain New York City's aging power grid. It presents a general process for analyzing historical grid ...
Missing: New York City
Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance.
We introduce a general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems.
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Rudin, C., Waltz, D., Anderson, R. N., Boulanger, A., Salleb-Aouissi, A., Chow, M., et al. (2012). Machine learning for the New York City power grid.