检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:温舒晴 张伟荣 杨志伟 李振喜 黄博巨 杨绪俊 Wen Shuqing;Zhang Weirong;Yang Zhiwei;Li Zhenxi;Huang Boju;Yang Xujun(Faculty of Urban Construction,Beijing University of Technology,Beijing,100124;Persagy Technology Co.,Ltd.,Beijing,100096;Haina Wanshang Property Management Co.,Ltd.,610095,Sichuan)
机构地区:[1]北京工业大学城市建设学部,北京100124 [2]博锐尚格科技股份有限公司,北京100096 [3]海纳万商物业管理有限公司,四川610095
出 处:《建设科技》2021年第23期37-43,共7页Construction Science and Technology
基 金:净零能耗建筑适宜技术研究与集成示范(2019YFE0100300)。
摘 要:商业建筑碳排放量受到气候、地理、经济水平的影响,为研究不同分类下商业建筑碳排放量的差异,制定合适的碳排放量指标与逐年降低比例,本研究整理了大量不同气候区及开业年份的商业建筑的实测能耗数据,在此基础之上,基于碳排放因子法、BP神经网络和回归拟合的方法,预测了不同分类商业建筑未来一年的碳排放量并分析了其发展趋势。结果显示,同一气候区下,纬度相差越大的商业建筑,对应的碳排放量指标差异也越大,且不同分类的商业建筑碳排放量都呈现出先逐渐降低后趋于平缓的发展趋势。Carbon emissions from commercial buildings are affected by climate,geography,and economic level.In order to study the differences of carbon emissions of commercial buildings under different classifications and formulate appropriate carbon emission indicators and annual reduction ratio,this study sorted out a large number of measured energy consumption data of commercial buildings in different climate areas and operation years.Based on the method of carbon emission factor,BP neural network and regression fitting,the carbon emission of different commercial buildings in the next year was predicted and its development trend was analyzed.The results show that in the same climate zone,the greater the latitude difference of commercial buildings,the greater the corresponding difference of carbon emissions index,and the carbon emissions of commercial buildings in different dimensions show a development trend of gradually reducing first and then tending to be flat.
分 类 号:TU201.5[建筑科学—建筑设计及理论]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.208