Show simple item record

dc.contributor.authorAbassi, Abdelfattah
dc.contributor.authorArid, Ahmed
dc.contributor.authorBenazza, Hussain
dc.date.accessioned2023-08-16T18:36:15Z
dc.date.available2023-08-16T18:36:15Z
dc.date.copyright4/3/2023 12:00:00 AM
dc.date.issued2023
dc.identifier.issn2642-6641
dc.identifier.otherjesbc_4_1_011004.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292199
dc.description.abstractThe study aims to analyze the patterns of home appliance use and energy consumption among Moroccan consumers using the MORED dataset. Machine learning algorithms and data mining techniques are applied to understand consumer behavior in terms of energy usage. The results provide insights into the inter-appliance association and peak hours, which will be used to design an Energy Demand Management System (EDMS) for Moroccan buildings in the future. The purpose of this research is to support the development of an effective EDMS and to encourage end-user involvement in energy management in Morocco.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleMoroccan Consumer Energy Consumption Itemsets and Inter-Appliance Associations Using Machine Learning Algorithms and Data Mining Techniques
dc.typeJournal Paper
dc.journal.volume4
dc.journal.issue1
dc.journal.titleASME Journal of Engineering for Sustainable Buildings and Cities
dc.identifier.doi10.1115/1.4062113
dc.journal.fristpage11004-1
dc.journal.lastpage11004-10
dc.page10
dc.treeASME Journal of Engineering for Sustainable Buildings and Cities:;2023:;volume( 004 ):;issue: 001
dc.contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record