摘要
低碳建筑是建筑行业不可避免的发展趋势,尤其是在全球变暖的危急时刻,必须对低碳建筑做出综合评价。从建筑的全生命周期出发,本文利用层次分析法(AHP)和BP神经网络法构建低碳建筑评价体系。结果显示:基于层次分析与BP神经网络的评价结果,要比传统层次分析法的评价结果更精确。表明BP神经网络法能有效降低层次分析法中主观因素带来的影响,提高评价结果的客观性。
Low carbon architecture is an inevitable developmental trend of the construction industry. Especially in a crisis of global warming, we must make a comprehensive evaluation of low carbon architecture. Starting from the full life cycle of the building, the article used AHP and BP neural network method to build the low-carbon architecture evaluation system. The results showed that： compared with the only AHP, the evaluation result based on AHP and BP neural network method is more accurate. The model would effectively reduce the influence of subiective factors and enhance the obiectivity of the evaluation results.
出处
《价值工程》
2015年第4期134-136,共3页
Value Engineering
关键词
低碳建筑
评价方法
层次分析法
BP神经网络
low-carbon architecture
assessment method
AHP（the analytic hierarchy process）
BP neural network
