Implementation of a long short-term memory transfer learning (lstm-tl)-based data-driven model for building energy demand forecasting

HIGHLIGHTS

• who: Dongsu Kim and colleagues from the Department of Architecture Engineering, Hanbat National University, Daejeon, Republic of Korea have published the Article: Implementation of a Long Short-Term Memory Transfer Learning (LSTM-TL)-Based Data-Driven Model for Building Energy Demand Forecasting, in the Journal: Sustainability 2023, 2340 of 25/01/2023
• what: Lastly a comparative analysis was carried out to investigate how the accuracy of LSTM prediction can be enhanced with the help of learning strategies. The results from this study show that the developed LSTM-TL model can achieve better performance than the . . .
  

   

  

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