CASIA OpenIR
Parallel Building: A Complex System Approach for Smart Building Energy Management
Almalaq, Abdulaziz1,2; Hao, Jun2; Zhang, Jun Jason2; Wang, Fei-Yue3,4
Source PublicationIEEE-CAA JOURNAL OF AUTOMATICA SINICA
ISSN2329-9266
2019-11-01
Volume6Issue:6Pages:1452-1461
Corresponding AuthorAlmalaq, Abdulaziz(a.almalaq@uoh.edu.sa)
AbstractThese 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.
KeywordACP theory artificial intelligence data acquisition deep learning (DL) energy consumption machine learning parallel energy prediction prediction algorithms smart grid
DOI10.1109/JAS.2019.1911768
WOS KeywordARTIFICIAL NEURAL-NETWORKS ; SUPPORT VECTOR MACHINES ; REGRESSION-ANALYSIS ; CONSUMPTION ; PREDICTION ; ENSEMBLES ; STORAGE
Indexed BySCI
Language英语
WOS Research AreaAutomation & Control Systems
WOS SubjectAutomation & Control Systems
WOS IDWOS:000503189200015
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/29434
Collection中国科学院自动化研究所
Corresponding AuthorAlmalaq, Abdulaziz
Affiliation1.Univ Hail, Dept Elect Engn, Engn Coll, Hail 55476, Saudi Arabia
2.Univ Denver, Ritchie Sch Engn & Comp Sci, Dept Elect & Comp Engn, Denver, CO 80208 USA
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
4.Natl Univ Def Technol, Res Ctr Mil Computat Expt & Parallel Syst Technol, Changsha 410073, Hunan, Peoples R China
Recommended Citation
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.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Almalaq, Abdulaziz]'s Articles
[Hao, Jun]'s Articles
[Zhang, Jun Jason]'s Articles
Baidu academic
Similar articles in Baidu academic
[Almalaq, Abdulaziz]'s Articles
[Hao, Jun]'s Articles
[Zhang, Jun Jason]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Almalaq, Abdulaziz]'s Articles
[Hao, Jun]'s Articles
[Zhang, Jun Jason]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.