Tuning Deep Neural Networks for Predicting Energy Consumption in Arid Climate Based on Buildings Characteristics
The dramatic growth in the number of buildings worldwide has led to an increase interest in predicting energy consumption, especially for the case of residential buildings. As the heating and cooling system highly affect the operation cost of buildings; it is worth investigating the development of m...
Enregistré dans:
Auteurs principaux: | Amal A. Al-Shargabi, Abdulbasit Almhafdy, Dina M. Ibrahim, Manal Alghieth, Francisco Chiclana |
---|---|
Format: | article |
Langue: | EN |
Publié: |
MDPI AG
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/586fd87ad23a4ca8987dd94f3f479249 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Energy Savings of Simultaneous Heating and Cooling System According to Indoor Set Temperature Changes in the Comfort Range
par: Dae-Uk Shin, et autres
Publié: (2021) -
Evaluation of Heating and Cooling Loads for a Well-Insulated Single-Family House under Variable Climate Pattern
par: Prozuments Aleksejs, et autres
Publié: (2021) -
Long-Term Policy Recommendations for Improving the Efficiency of Heating and Cooling
par: Laktuka Krista, et autres
Publié: (2021) -
Electricity Theft Detection in Power Consumption Data Based on Adaptive Tuning Recurrent Neural Network
par: Guoying Lin, et autres
Publié: (2021) -
Analysis of the Heat Pump Market in Europe with a Special Regard to France, Spain, Poland and Lithuania
par: Witkowska Agata, et autres
Publié: (2021)