4.6 Article

Carbon reduction assessment of public buildings based on Apriori algorithm and intelligent big data analysis

期刊

SOFT COMPUTING
卷 -, 期 -, 页码 -

出版社

SPRINGER
DOI: 10.1007/s00500-023-08405-4

关键词

Apriori algorithm; Big data analysis; Building energy conservation; Carbon reduction assessment; Conserve energy and reduce emissions

向作者/读者索取更多资源

With the continuous progress of urbanization, public buildings are facing various environmental problems, such as high carbon emissions and energy consumption, leading to significant environmental pollution. This paper integrates intelligent big data technology and Apriori algorithm to design and construct a carbon reduction measurement system for public buildings. By analyzing the entire life cycle of the buildings, the system calculates the energy consumption projects and converts them into carbon footprint indicators. It performs a quantitative assessment of the environmental pollution level and obtains carbon reduction assessment data based on the carbon emission factors. The results can be used for designing and implementing energy conservation and emission reduction policies.
Today, with the continuous progress of urbanization, public buildings have many environmental problems. Their high carbon emissions and energy consumption have caused considerable environmental pollution. Based on the analysis of the whole life cycle of public buildings, it can be seen from the results that due to its long time span, the service life will cause more pollution to the environment, high energy consumption and carbon emissions. In this environment, this paper completes the design and construction of carbon reduction measurement system for public buildings by combining intelligent big data technology and Apriori algorithm. The system mainly analyzes the whole life cycle of the building to calculate all energy consumption projects of the building, converts them into carbon footprint indicators, and uses the indicators to complete the quantitative assessment of environmental pollution level for public buildings in the whole life cycle, and obtains the carbon reduction assessment data of the building in the operating cycle in combination with the carbon emission factors of energy and electricity. The results of quantitative data analysis can be used for the design and arrangement of energy conservation and emission reduction policies, which can be realized by changing the lighting and ventilation, peripheral protection, shape coefficient and rainwater circulation of buildings. This paper conducts carbon reduction assessment for public buildings by integrating intelligent big data and Apriori algorithm.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据