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A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey

The Energy Management System (EMS) is the cost-effectiveness, robustness, and flexible approach for energy efficiency management (EEM). Data-Driven Energy Efficiency Management (D2EEM) is a recent advancement in EMS. The D2EEM is the blend of data science and artificial intelligence for EEM. Due to...

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Main Authors: Akhtar, Shamim, Muhamad Zahim, Sujod, Hussain Rizvi, Syed Sajjad
格式: Conference or Workshop Item
语言:English
English
出版: IEEE 2021
主题:
QA76 Computer software
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
在线阅读:http://umpir.ump.edu.my/id/eprint/38589/1/A%20Novel%20Deep%20Learning%20Architecture%20for%20Data-Driven%20Energy%20Efficiency%20Management%20%28D2EEM%29%20-%20Systematic%20Survey.pdf
http://umpir.ump.edu.my/id/eprint/38589/2/IEEE_A_Novel_Deep_Learning_Architecture_for_Data-Driven_Energy_Efficiency_Management_D2EEM_-_Systematic_Survey.pdf
http://umpir.ump.edu.my/id/eprint/38589/
https://doi.org/10.1109/ICEET53442.2021.9659737
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id my.ump.umpir.38589
record_format eprints
spelling my.ump.umpir.385892023-09-08T03:42:41Z http://umpir.ump.edu.my/id/eprint/38589/ A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey Akhtar, Shamim Muhamad Zahim, Sujod Hussain Rizvi, Syed Sajjad QA76 Computer software T Technology (General) TK Electrical engineering. Electronics Nuclear engineering The Energy Management System (EMS) is the cost-effectiveness, robustness, and flexible approach for energy efficiency management (EEM). Data-Driven Energy Efficiency Management (D2EEM) is a recent advancement in EMS. The D2EEM is the blend of data science and artificial intelligence for EEM. Due to the highly tolerant to the performance plateau and unconstraint to the feature extraction, Deep Learning (DL) facilitates handling big data-driven problems of EEM. To the best of the knowledge, the accurate and robust D2EEM is the pressing need. Moreover, the accurate pre-trained DL network for EEM is not available in the recent literature. In this work, a comprehensive study is presented to devise a D2EEM. Moreover, the architecture is suggested in connection to the research gap. IEEE 2021 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/38589/1/A%20Novel%20Deep%20Learning%20Architecture%20for%20Data-Driven%20Energy%20Efficiency%20Management%20%28D2EEM%29%20-%20Systematic%20Survey.pdf pdf en http://umpir.ump.edu.my/id/eprint/38589/2/IEEE_A_Novel_Deep_Learning_Architecture_for_Data-Driven_Energy_Efficiency_Management_D2EEM_-_Systematic_Survey.pdf Akhtar, Shamim and Muhamad Zahim, Sujod and Hussain Rizvi, Syed Sajjad (2021) A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey. In: 7th International Conference on Engineering and Emerging Technologies, ICEET 2021, 27-28 October 2021 , Istanbul, Turkey. (176217). ISBN 9781665427142 https://doi.org/10.1109/ICEET53442.2021.9659737
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA76 Computer software
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle QA76 Computer software
T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Akhtar, Shamim
Muhamad Zahim, Sujod
Hussain Rizvi, Syed Sajjad
A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey
description The Energy Management System (EMS) is the cost-effectiveness, robustness, and flexible approach for energy efficiency management (EEM). Data-Driven Energy Efficiency Management (D2EEM) is a recent advancement in EMS. The D2EEM is the blend of data science and artificial intelligence for EEM. Due to the highly tolerant to the performance plateau and unconstraint to the feature extraction, Deep Learning (DL) facilitates handling big data-driven problems of EEM. To the best of the knowledge, the accurate and robust D2EEM is the pressing need. Moreover, the accurate pre-trained DL network for EEM is not available in the recent literature. In this work, a comprehensive study is presented to devise a D2EEM. Moreover, the architecture is suggested in connection to the research gap.
format Conference or Workshop Item
author Akhtar, Shamim
Muhamad Zahim, Sujod
Hussain Rizvi, Syed Sajjad
author_facet Akhtar, Shamim
Muhamad Zahim, Sujod
Hussain Rizvi, Syed Sajjad
author_sort Akhtar, Shamim
title A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey
title_short A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey
title_full A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey
title_fullStr A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey
title_full_unstemmed A Novel Deep Learning Architecture for Data-Driven Energy Efficiency Management (D2EEM) - Systematic Survey
title_sort novel deep learning architecture for data-driven energy efficiency management (d2eem) - systematic survey
publisher IEEE
publishDate 2021
url http://umpir.ump.edu.my/id/eprint/38589/1/A%20Novel%20Deep%20Learning%20Architecture%20for%20Data-Driven%20Energy%20Efficiency%20Management%20%28D2EEM%29%20-%20Systematic%20Survey.pdf
http://umpir.ump.edu.my/id/eprint/38589/2/IEEE_A_Novel_Deep_Learning_Architecture_for_Data-Driven_Energy_Efficiency_Management_D2EEM_-_Systematic_Survey.pdf
http://umpir.ump.edu.my/id/eprint/38589/
https://doi.org/10.1109/ICEET53442.2021.9659737
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score 13.251813

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