Performance evaluation of short-term cross-building energy predictions using deep transfer learning strategies
Energy and Buildings(2022)
Abstract
•3 DTL strategies obtain 75% PIRs than LSTM for data shortage BEP tasks in OFs and UCs.•Recommend Fine-tune for next few weeks BEP by balance between time cost and performance.•Recommend DANN for nearly a year BEP by outperformed accuracy than Fine-tune, DaNN.•Evaluate DTL prediction accuracy by varying available training data in both source and target buildings.
MoreTranslated text
Key words
Building energy prediction (BEP),Cross-building,Deep transfer learning (DTL),Domain adversarial neural network (DANN),Fine-tune,Performance improvement ratio (PIR)
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined