A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings

Detalhes bibliográficos
Autor(a) principal: Abdelaziz, Ahmed
Data de Publicação: 2023
Outros Autores: Santos, Vítor, Dias, Miguel Sales
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/158925
Resumo: Abdelaziz, A., Santos, V., & Dias, M. S. (2023). A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings. International Journal of Advanced Computer Science and Applications, 14(9), 136-152. [15]. https://doi.org/10.14569/IJACSA.2023.0140915 --- This work has been supported by Portuguese funds through FCT-Fundação para a Ciência e Tecnologia, Instituto Público (IP), under the project FCT UIDB/04466/2020 by Information Sciences and Technologies and Architecture Research Center (ISTAR-IUL), and this work has also been supported by Information Management Research Center (MagIC)-Information Management School of NOVA University Lisbon
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spelling A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public BuildingsEnergy consumption in public buildingsgenetic algorithmK-meansprincipal component analysisself-organizing mapComputer Science(all)SDG 7 - Affordable and Clean EnergyAbdelaziz, A., Santos, V., & Dias, M. S. (2023). A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings. International Journal of Advanced Computer Science and Applications, 14(9), 136-152. [15]. https://doi.org/10.14569/IJACSA.2023.0140915 --- This work has been supported by Portuguese funds through FCT-Fundação para a Ciência e Tecnologia, Instituto Público (IP), under the project FCT UIDB/04466/2020 by Information Sciences and Technologies and Architecture Research Center (ISTAR-IUL), and this work has also been supported by Information Management Research Center (MagIC)-Information Management School of NOVA University LisbonRecently, intelligent applications gained a significant role in the energy management of public buildings due to their ability to enhance energy consumption performance. Energy management of these buildings represents a big challenge due to their unexpected energy consumption characteristics and the deficiency of design guidelines for energy efficiency and sustainability solutions. Therefore, an analysis of energy consumption patterns in public buildings becomes necessary. This reveals the significance of understanding and classifying energy consumption patterns in these buildings. This study seeks to find the optimal intelligent technique for classifying energy consumption of public buildings into levels (e.g., low, medium, and high), find the critical factors that influence energy consumption, and finally, find the scientific rules (If-Then rules) to help decision-makers for determining the energy consumption level in each building. To achieve the objectives of this study, correlation coefficient analysis was used to determine critical factors that influence on energy consumption of public buildings; two intelligent models were used to determine the number of clusters of energy consumption patterns which are Self Organizing Map (SOM) and Batch-SOM based on Principal Component Analysis (PCA). SOM outperforms Batch-SOM in terms of quantization error. The quantization error of SOM and Batch-SOM is 8.97 and 9.24, respectively. K-means with a genetic algorithm were used to predict cluster levels in each building. By analyzing cluster levels, If-Then rules have been extracted, so needs that decision-makers determine the most energyconsuming buildings. In addition, this study helps decisionmakers in the energy field to rationalize the consumption of occupants of public buildings in the times that consume the most energy and change energy suppliers to those buildings.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNAbdelaziz, AhmedSantos, VítorDias, Miguel Sales2023-10-13T22:19:25Z2023-102023-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article17application/pdfhttp://hdl.handle.net/10362/158925eng2158-107XPURE: 73746476https://doi.org/10.14569/IJACSA.2023.0140915info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:41:26Zoai:run.unl.pt:10362/158925Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:57:20.911549Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings
title A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings
spellingShingle A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings
Abdelaziz, Ahmed
Energy consumption in public buildings
genetic algorithm
K-means
principal component analysis
self-organizing map
Computer Science(all)
SDG 7 - Affordable and Clean Energy
title_short A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings
title_full A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings
title_fullStr A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings
title_full_unstemmed A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings
title_sort A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings
author Abdelaziz, Ahmed
author_facet Abdelaziz, Ahmed
Santos, Vítor
Dias, Miguel Sales
author_role author
author2 Santos, Vítor
Dias, Miguel Sales
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Abdelaziz, Ahmed
Santos, Vítor
Dias, Miguel Sales
dc.subject.por.fl_str_mv Energy consumption in public buildings
genetic algorithm
K-means
principal component analysis
self-organizing map
Computer Science(all)
SDG 7 - Affordable and Clean Energy
topic Energy consumption in public buildings
genetic algorithm
K-means
principal component analysis
self-organizing map
Computer Science(all)
SDG 7 - Affordable and Clean Energy
description Abdelaziz, A., Santos, V., & Dias, M. S. (2023). A Proposed Intelligent Model with Optimization Algorithm for Clustering Energy Consumption in Public Buildings. International Journal of Advanced Computer Science and Applications, 14(9), 136-152. [15]. https://doi.org/10.14569/IJACSA.2023.0140915 --- This work has been supported by Portuguese funds through FCT-Fundação para a Ciência e Tecnologia, Instituto Público (IP), under the project FCT UIDB/04466/2020 by Information Sciences and Technologies and Architecture Research Center (ISTAR-IUL), and this work has also been supported by Information Management Research Center (MagIC)-Information Management School of NOVA University Lisbon
publishDate 2023
dc.date.none.fl_str_mv 2023-10-13T22:19:25Z
2023-10
2023-10-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/158925
url http://hdl.handle.net/10362/158925
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2158-107X
PURE: 73746476
https://doi.org/10.14569/IJACSA.2023.0140915
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 17
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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