Modeling Weather Impact on a Secondary Electrical Grid.

Procedia Computer Science(2014)

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摘要
Weather can cause problems for underground electrical grids by increasing the probability of serious “manhole events” such as fires and explosions. In this work, we compare a model that incorporates weather features associated with the dates of serious events into a single logistic regression, with a more complex approach that has three interdependent log linear models for weather, baseline manhole vulnerability, and vulnerability of manholes to weather. The latter approach more naturally incorporates the dependencies between the weather, structure properties, and structure vulnerability.
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关键词
Secondary Electrical Grid,Machine Learning,Expectation-Maximization,Log-Linear Model,Semantic Dependency,Interpretable Models
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