Identifying the most influential parameters in predicting lighting energy consumption in office buildings using data-driven method
Author:
Publisher
Elsevier BV
Subject
Mechanics of Materials,Safety, Risk, Reliability and Quality,Building and Construction,Architecture,Civil and Structural Engineering
Reference72 articles.
1. A review of data-driven building energy consumption prediction studies;Amasyali;Renew. Sustain. Energy Rev.,2018
2. Methodology for retrofitting energy in existing office buildings using building information modelling programs;Danial;Ain Shams Eng. J.,2023
3. Modeling individual's light switching behavior to understand lighting energy use of office building;Wang;Energy Proc.,2016
4. Analysis of lighting occupancy sensor installation in building renovation using agent-based modeling of occupant behavior;Norouziasl,2019
5. Light-stacking strengthened fusion based building energy consumption prediction framework via variable weight feature selection;Sun;Appl. Energy,2021
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A review on the energy in buildings: Current research focus and future development direction;Heliyon;2024-06
2. Enhancing multi-scenario data-driven energy consumption prediction in campus buildings by selecting appropriate inputs and improving algorithms with attention mechanisms;Energy and Buildings;2024-05
3. Enhancing building energy consumption prediction introducing novel occupant behavior models with sparrow search optimization and attention mechanisms: A case study for forty-five buildings in a university community;Energy;2024-05
4. How population aging promotes carbon emission reduction in Chinese cities: The chain mediating role of industrial upgrading and energy conservation;Journal of Environmental Management;2024-03
5. Evaluation of Design Parameters for Daylighting Performance in Secondary School Classrooms Based on Field Measurements and Physical Simulations: A Case Study of Secondary School Classrooms in Guangzhou;Buildings;2024-02-28
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3