Enabling alarm-based fault prediction for smart meters in district heating systems: a danish case study

HIGHLIGHTS

• What: That is because for this work, given the available time series data from smart meters and the overall goal, the use of occurrence-time prediction is the most fitting. By using classification, you also explicitly tell the model what to learn and can be certain the model has the same goal as you. For these two types of methods, you also assume that the models have the same goals as you and will try to predict what you want, and more thorough testing is needed to validate that. The authors focus on detecting the alarms on . . .
  

   

  

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