Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Energy Consumption Prediction for Buildings
Several research projects have been conducted and published on the characteristics and Energy Performance Index (EPI) of residences in Florida. An artificial neural network that allows for the prediction of energy consumption for residences located in climates similar to that of Central Florida has been developed. By using the ability of artificial neural networks to predict energy consumption, residential designers/builders can significantly help advance the goals of reducing the monthly cost of new housing and reducing the environmental impact and energy use of new housing. The methodology used to develop the Energy Performance and Consumption artificial neural network can be adopted and applied in any climate, whether nationally or internationally, upon the collection of the appropriate relevant data. The results can be used to design and build houses with lower energy use, which results in a lower cost of home ownership and less detrimental environmental impact.
Energy Consumption Prediction for Buildings
Several research projects have been conducted and published on the characteristics and Energy Performance Index (EPI) of residences in Florida. An artificial neural network that allows for the prediction of energy consumption for residences located in climates similar to that of Central Florida has been developed. By using the ability of artificial neural networks to predict energy consumption, residential designers/builders can significantly help advance the goals of reducing the monthly cost of new housing and reducing the environmental impact and energy use of new housing. The methodology used to develop the Energy Performance and Consumption artificial neural network can be adopted and applied in any climate, whether nationally or internationally, upon the collection of the appropriate relevant data. The results can be used to design and build houses with lower energy use, which results in a lower cost of home ownership and less detrimental environmental impact.
Energy Consumption Prediction for Buildings
Issa, Raja R. A. (Autor:in) / Flood, Ian (Autor:in)
Eighth International Conference on Computing in Civil and Building Engineering (ICCCBE-VIII) ; 2000 ; Stanford, California, United States
04.08.2000
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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