City-scale single family residential building energy consumption prediction using genetic algorithm-based Numerical Moment Matching technique
Author:
Funder
National Science Foundation
Publisher
Elsevier BV
Subject
Building and Construction,Geography, Planning and Development,Civil and Structural Engineering,Environmental Engineering
Reference65 articles.
1. Urban building energy modeling - a review of a nascent field;Reinhart;Build. Environ.,2016
2. Modeling and forecasting energy consumption for heterogeneous buildings using a physical-statistical approach;Lü;Appl. Energy,2015
3. Energy refurbishment of existing buildings through the use of phase change materials: energy savings and indoor comfort in the cooling season;Ascione;Appl. Energy,2014
4. Evaluation of the causes and impact of outliers on residential building energy use prediction using inverse modeling;Do;Build. Environ.,2018
5. Residential building energy Consumption : a review of energy data availability , characteristics , and energy performance prediction methods;Do;Curr. Sustain. Energy Reports,2018
Cited by 33 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. Thermal performance of packed-bed latent heat storage tank integrated with flat-plate collectors under intermittent loads of building heating;Energy;2024-07
2. Predicting Energy Consumption Using Stacked LSTM Snapshot Ensemble;Big Data Mining and Analytics;2024-06
3. Analysis of Internal Conditions and Energy Consumption during Winter in an Apartment Located in a Tenement Building in Poland;Sustainability;2024-05-09
4. 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
5. 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
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