Comparison of machine learning techniques for predicting energy loads in buildings

Comparison of machine learning techniques for predicting energy loads in buildings

Machine learning methods can be used to help design energy-efficient buildings reducing energy loads while maintaining the desired internal temperature. They work by estimating a response from a set of inputs such as building geometry, material properties, project costs, local weather conditions, as...

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主要な著者:	Duarte, Grasiele Regina, Fonseca, Leonardo Goliatt da, Goliatt, Priscila Vanessa Zabala Capriles, Lemonge, Afonso Celso de Castro
フォーマット:	Online
言語:	eng
出版事項:	ANTAC - Associação Nacional de Tecnologia do Ambiente Construído 2017
オンライン･アクセス:	https://seer.ufrgs.br/ambienteconstruido/article/view/69635
タグ:	タグ追加タグなし, このレコードへの初めてのタグを付けませんか!

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