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基于改进 AHP-FCE 方法的绿色智能建筑评价研究。

Research on Evaluation of Green Smart Building Based on Improved AHP-FCE Method.

机构信息

School of Economics and Management, Anhui Jianzhu University, Hefei, Anhui, China.

出版信息

Comput Intell Neurosci. 2021 Nov 26;2021:5485671. doi: 10.1155/2021/5485671. eCollection 2021.

DOI:10.1155/2021/5485671
PMID:34868293
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8642022/
Abstract

With the accelerated pace of urbanization, green buildings and green smart buildings gradually come into people's vision and are highly valued by all sectors of society on the premise of meeting sustainable development strategy. Firstly, this paper selects 7 first-level index factors and 20 second-level index factors to establish the green smart building evaluation system. Secondly, this paper uses the analytic hierarchy process-fuzzy comprehensive evaluation (AHP-FCE) method to determine the weight of each secondary index. Finally, the feasibility of the evaluation system is verified by case analysis, and some suggestions on green smart building are put forward.

摘要

随着城市化进程的加速,绿色建筑和绿色智能建筑逐渐进入人们的视野,并在满足可持续发展战略的前提下受到社会各界的高度重视。首先,本文选择了 7 个一级指标因素和 20 个二级指标因素来建立绿色智能建筑评价体系。其次,本文采用层次分析法-模糊综合评价(AHP-FCE)方法确定各二级指标的权重。最后,通过案例分析验证了评价体系的可行性,并提出了一些绿色智能建筑的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84d5/8642022/9748934490ea/CIN2021-5485671.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84d5/8642022/297ffc77c8c5/CIN2021-5485671.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84d5/8642022/72515a6d7bf9/CIN2021-5485671.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84d5/8642022/9748934490ea/CIN2021-5485671.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84d5/8642022/297ffc77c8c5/CIN2021-5485671.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84d5/8642022/72515a6d7bf9/CIN2021-5485671.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84d5/8642022/9748934490ea/CIN2021-5485671.003.jpg

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