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Creators/Authors contains: "Huang, Shuchen"

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  1. In this paper, a cascading failure interaction learning method is proposed for real utility outage data. For better revealing the structure, we reorganize the failure interaction matrix based on Louvain community detection. A deep convolutional generative adversarial network (DCGAN) based method is then proposed to learn the implicit features for failure propagation in the interaction matrix. A systematic method is further developed to evaluate the performance of the learning method on missing interaction recovery and new interaction discovery. The effectiveness of the proposed method is validated on the 14-year real utility outage data from Bonneville Power Administration. 
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