A transfer learning framework using spatiotemporal graph convolutional network and adversarial domain adaptation for cross-district building group energy predictionOA
A transfer learning framework using spatiotemporal graph convolutional network and adversarial domain adaptation for cross-district building group energy prediction
Yingjun Ruan;Yamei Ma;Hua Meng;Tingting Xu;Yuting Yao;Fanyue Qian;Chaoliang Wang;Wei Liu
College of Mechanical and Energy Engineering,Tongji University,Shanghai 200092,ChinaCollege of Mechanical and Energy Engineering,Tongji University,Shanghai 200092,ChinaCollege of Mechanical and Energy Engineering,Tongji University,Shanghai 200092,ChinaCollege of Mechanical and Energy Engineering,Tongji University,Shanghai 200092,ChinaCollege of Mechanical and Energy Engineering,Tongji University,Shanghai 200092,ChinaCollege of Mechanical and Energy Engineering,Tongji University,Shanghai 200092,ChinaState Grid Zhejiang Marketing Service Centre,Hangzhou 310014,ChinaState Grid Zhejiang Marketing Service Centre,Hangzhou 310014,China
data scarcitydistrict building energy consumption predictioncross-district transfertransfer learningspatiotemporal graph convolutional networkadversarial domain adaptation
data scarcitydistrict building energy consumption predictioncross-district transfertransfer learningspatiotemporal graph convolutional networkadversarial domain adaptation
《建筑模拟（英文版）》 2026 (1)
235-255,21
This research is supported by the National Key R&D Program of China(No.2023YFC3807100).
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