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Energy-saving technology of BIM green buildings using fractional differential equation

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13 dic 2021
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Fig. 1

Comparison of actual and forecasted values of each model.
Comparison of actual and forecasted values of each model.

Fig. 2

Distribution scatterplot of prediction and measurement of residential average natural gas consumption.
Distribution scatterplot of prediction and measurement of residential average natural gas consumption.

Fig. 3

Distribution scatterplot of predicted and measured values of average residential power consumption.
Distribution scatterplot of predicted and measured values of average residential power consumption.

Energy-saving potential after residential renovation of different years and types of buildings_

Building life Building type
<2016 2016–2017 2017–2018 >2018 Detached house Semidetached dwelling Row house Villa
Energy-saving rate, % 56 24 17 3 3 12 20 29

Calculation results of the evaluation indexes of each model_

Error GM(1,1) model GM-BP neural network model

Maximum relative error, absolute value, Emax, % 46.12 0.47
Average relative error, εave, % 7.69 0.08
RMSE (×106) 66.10 1.46
Lingua:
Inglese
Frequenza di pubblicazione:
1 volte all'anno
Argomenti della rivista:
Scienze biologiche, Scienze della vita, altro, Matematica, Matematica applicata, Matematica generale, Fisica, Fisica, altro