低碳目标约束下公共建筑绿色施工节能减排潜力预测模型  被引量:3

Prediction Model of Energy Saving and Emission Reduction Potential of Green Construction in Public Buildings Under Low Carbon Target Constraints

在线阅读下载全文

作  者:汤海洋[1] TANG Haiyang(China Railway Construction Corporation Limited,Beijing 100080,China)

机构地区:[1]中国铁建股份有限公司,北京100080

出  处:《铁道建筑技术》2023年第8期180-184,共5页Railway Construction Technology

基  金:中国铁建股份有限公司科技研究开发计划项目(2022-G11)。

摘  要:目前常规的公共建筑绿色施工节能减排潜力预测模型主要以能源消耗量为目标函数构建多元回归预测模型。由于缺乏对节能减排潜力量化指标的分类讨论,导致预测效果不佳。对此,提出低碳目标约束下公共建筑绿色施工节能减排潜力预测模型。结合相关系数法,对影响模型预估效果的要素进行量化分析,并选取节能率和减排率作为潜力预测模型的量化指标,分别对节能潜力以及减排潜力进行测算。通过实验对提出的模型进行预测精度检验,结果表明,模型均方根误差值较低,说明其具备更为理想的预测精度。The current conventional prediction model of energy saving and emission reduction potential for green construction of public buildings mainly takes energy consumption as the objective function and constructs a multiple regression prediction model,which leads to poor prediction due to the lack of discussion on the classification of quantitative indicators of energy saving and emission reduction potential.In this regard,the prediction model of energy saving and emission reduction potential of green construction in public buildings under low carbon target constraints is proposed.Combined with the correlation coefficient method,the elements affecting the prediction effect of the model were quantified and analyzed,and the energy saving rate and emission reduction rate were selected as the quantitative indicators of the potential prediction model to measure the energy saving potential as well as the emission reduction potential respectively.The proposed model was tested for prediction accuracy through the experiment.The experimental results show that the model has a lower root mean square error value,indicating that it has a more desirable prediction accuracy.

关 键 词:绿色施工 低碳目标 节能减排潜力 预测模型 量化指标 

分 类 号:TU712[建筑科学—建筑技术科学] TU242

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象