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Parallel Building: A Complex System Approach for Smart Building Energy Management

文献类型：期刊论文

作者Almalaq, Abdulaziz2,3; Hao, Jun3; Zhang, Jun Jason3; Wang, Fei-Yue1,4
刊名IEEE-CAA JOURNAL OF AUTOMATICA SINICA
出版日期2019-11-01
卷号6期号:6页码:1452-1461
关键词ACP theory artificial intelligence data acquisition deep learning (DL) energy consumption machine learning parallel energy prediction prediction algorithms smart grid
ISSN号2329-9266
DOI10.1109/JAS.2019.1911768
通讯作者Almalaq, Abdulaziz(a.almalaq@uoh.edu.sa)
英文摘要These days' smart buildings have high intensive information and massive operational parameters, not only extensive power consumption. With the development of computation capability and future 5G, the ACP theory (i.e., artificial systems, computational experiments, and parallel computing) will play a much more crucial role in modeling and control of complex systems like commercial and academic buildings. The necessity of making accurate predictions of energy consumption out of a large number of operational parameters has become a crucial problem in smart buildings. Previous attempts have been made to seek energy consumption predictions based on historical data in buildings. However, there are still questions about parallel building consumption prediction mechanism using a large number of operational parameters. This article proposes a novel hybrid deep learning prediction approach that utilizes long short-term memory as an encoder and gated recurrent unit as a decoder in conjunction with ACP theory. The proposed approach is tested and validated by real-world dataset, and the results outperformed traditional predictive models compared in this paper.
WOS关键词ARTIFICIAL NEURAL-NETWORKS ; SUPPORT VECTOR MACHINES ; REGRESSION-ANALYSIS ; CONSUMPTION ; PREDICTION ; ENSEMBLES ; STORAGE
WOS研究方向Automation & Control Systems
语种英语
WOS记录号WOS:000503189200015
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://ir.ia.ac.cn/handle/173211/29433]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者Almalaq, Abdulaziz
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Hail, Dept Elect Engn, Engn Coll, Hail 55476, Saudi Arabia
3.Univ Denver, Ritchie Sch Engn & Comp Sci, Dept Elect & Comp Engn, Denver, CO 80208 USA
4.Natl Univ Def Technol, Res Ctr Mil Computat Expt & Parallel Syst Technol, Changsha 410073, Hunan, Peoples R China
推荐引用方式
GB/T 7714		 Almalaq, Abdulaziz,Hao, Jun,Zhang, Jun Jason,et al. Parallel Building: A Complex System Approach for Smart Building Energy Management[J]. IEEE-CAA JOURNAL OF AUTOMATICA SINICA,2019,6(6):1452-1461.
APA Almalaq, Abdulaziz,Hao, Jun,Zhang, Jun Jason,&Wang, Fei-Yue.(2019).Parallel Building: A Complex System Approach for Smart Building Energy Management.IEEE-CAA JOURNAL OF AUTOMATICA SINICA,6(6),1452-1461.
MLA Almalaq, Abdulaziz,et al."Parallel Building: A Complex System Approach for Smart Building Energy Management".IEEE-CAA JOURNAL OF AUTOMATICA SINICA 6.6(2019):1452-1461.

入库方式： OAI收割

来源：自动化研究所

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