Fig 1.
Flowchart of building energy efficiency optimization based on BIM data and deep learning.
Fig 2.
Schematic of GNN architecture in building energy efficiency optimization.
Fig 3.
Architecture of the transformer based temporal model.
Fig 4.
Application framework of Generative Adversarial Network (GAN) in building energy efficiency optimization.
Fig 5.
Schematic diagram of the building energy efficiency optimization experiment.
Fig 6.
Energy consumption results of the research institute.
Fig 7.
Visualizing the comparison of energy efficiency metrics for multiple models across four datasets.
Table 1.
Comparison of energy efficiency metrics for various models based on the BIM-ECA and NEBULA datasets.
Table 2.
Comparison of energy efficiency metrics for various models based on the BEC and BIM-BEM datasets.
Fig 8.
Visualization of training time, inference time, and model parameters for various building energy - efficiency optimization models across four datasets.
Table 3.
Comparison of training time, inference time, and model parameters for various building energy - efficiency optimization models on the BIM-ECA and NEBULA datasets.
Table 4.
Comparison of training time, inference time, and model parameters for various building energy - efficiency optimization models on the BEC and BIM-BEM datasets.
Table 5.
Comparison of Model Performance on BIM-ECA, NEBULA, BEC, and BIM-BEM Datasets.
Fig 9.
Visualization of energy efficiency comparison of different model architectures across four datasets, showing energy saving rate and energy utilization rate.
Table 6.
Energy efficiency comparison of different model architectures on the BIM-ECA and NEBULA datasets, based on energy saving rate and energy utilization rate.
Table 7.
Energy efficiency comparison of different model architectures on the BEC and BIM-BEM datasets, based on energy saving rate and energy utilization rate.
Fig 10.
Visualization of model training time, inference time, and parameter scale for the BEC and BIM-BEM datasets.
Table 8.
Details of model training time, inference time, and parameter scale for the BIM-ECAG and NEBULA datasets.
Table 9.
Details of model training time, inference time, and parameter scale for the BEC and BIM-BEM datasets.