技术中心

【英文篇名】 Mode selection for energy efficiency retrofit of existing residential buildings based on BP artificial neural network 【作者中文名】 孙金颖; 武涌; 刘长滨; 【作者英文名】 Sun Jinying★; Wu Yong and Liu Changbin★ Harbin Institute of Technology; Harbin; China; 【作者单位】 哈尔滨工业大学; 建设部科学技术司; 北京建筑工程学院; 【文献出处】 暖通空调, Heating Ventilating 节能改造; 评价; 模式选择; BP; 人工神经网络; 【英文关键词】 existing residential buildings; energy efficient retrofit; appraisement; mode selection; back propagation; artificial neural network; 【摘要】 通过分析国内外既有居住建筑节能改造实例,确定了关键影响因素指标体系。采用BP神经网络建立了既有居住建筑节能改造评价模型,并提出了适合我国既有居住建筑节能改造的模式。 【英文摘要】 According to the analysis on examples at home and abroad of energy efficiency retrofit of existing residential buildings,determines the key influence factors.Creates the appraisement model based on BP artificial neural network,and proposes some modes suitable for the present conditions in China.