Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning

Data-driven models are widely used for building-energy predictions (BEPs). In practice, these models may fail when the available data on the target building is insufficient. Transfer learning (TL), where useful knowledge from information-rich source buildings with sufficient data is learned to enhan...

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Veröffentlicht in:	Energy (Oxford) 2024-07, Vol.299, p.131395, Article 131395
Hauptverfasser:	Li, Guannan, Wu, Yubei, Yoon, Sungmin, Fang, Xi
Format:	Artikel
Sprache:	eng
Schlagworte:	Building-energy prediction (BEP) data collection Data similarity domain Domain adversarial neural network (DANN) energy ex ante analysis genome model validation prediction Source domain selection Transfer learning (TL) Transferability assessment
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