Machine learning approaches for estimating commercial building energy consumption-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Machine learning approaches for estimating commercial building energy consumption

Published:2017-12 Issue: Volume:208 Page:889-904
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Robinson Caleb^ORCID,Dilkina Bistra,Hubbs Jeffrey^ORCID,Zhang Wenwen,Guhathakurta Subhrajit,Brown Marilyn A.,Pendyala Ram M.

Funder

Georgia Tech Strategic Energy Institute

CRISP: Sustainable and Resilient Design of Interdependent Water and Energy Systems at the Infrastructure-Human-Resource Nexus

COMPUSTNET: Expanding Horizons of Computational Sustainability

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference46 articles.

1. Impacts of urban form on future us passenger-vehicle greenhouse gas emissions;Hankey;Energy Policy,2010

2. The geography of metropolitan carbon footprints;Brown;Pol Soc,2009

3. Comparing high and low residential density: life-cycle analysis of energy use and greenhouse gas emissions;Norman;J Urban Plan Develop,2006

4. Life-cycle energy implications of different residential settings: recognizing buildings, travel, and public infrastructure;Nichols;Energy Policy,2014

5. Impact of urban form on energy use in central city and suburban neighborhoods: lessons from the phoenix metropolitan region;Guhathakurta;Energy Proc,2015

Cited by 335 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. Evaluating missing data handling methods for developing building energy benchmarking models;Energy;2024-11

2. Residential building energy consumption estimation: A novel ensemble and hybrid machine learning approach;Expert Systems with Applications;2024-10

3. Examining the non-linear relationship between urban form and air temperature at street level: A case of Hong Kong;Building and Environment;2024-10

4. Energy consumption prediction and energy-saving suggestions of public buildings based on machine learning;Energy and Buildings;2024-10

5. Holistic investigation for historical heritage revitalization through an innovative geothermal system;Applied Energy;2024-10

同舟云学术

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