Prediction method of intelligent building electricity consumption based on deep learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Cognitive Neuroscience,Computer Vision and Pattern Recognition,Mathematics (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s12065-023-00815-5.pdf
Reference31 articles.
1. Neto AH, Fiorelli FAS (2008) Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption. Energy Build 40(12):2169–2176
2. Javed S, Claesson J (2011) New analytical and numerical solutions for the short-term analysis of vertical ground heat exchangers. ASHRAE Trans 117(1):3
3. Amasyali K, El-Gohary NM (2018) A review of data-driven building energy consumption prediction studies. Renew Sustain Energy Rev 81:1192–1205
4. Laurinec P, Lucká M (2018) Clustering-based forecasting method for individual consumers electricity load using time series representations. Open Comput Sci 8(1):38–50
5. Laurinec P, Lóderer M, Vrablecová P, Lucká M, Rozinajová V, Ezzeddine AB (2016), December Adaptive time series forecasting of energy consumption using optimized cluster analysis. In: 2016 IEEE 16th international conference on data mining workshops (ICDMW), IEEE, pp. 398–405
Cited by 2 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 of Research on Building Energy Consumption Prediction Models Based on Artificial Neural Networks;Sustainability;2024-09-07
2. An Empirical Analysis of the Long Short Term Memory and Temporal Fusion Transformer Models on Regional Air Quality Forecast;2023 International Conference on Cyber-Physical Social Intelligence (ICCSI);2023-10-20
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