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contributor authorAbassi, Abdelfattah
contributor authorArid, Ahmed
contributor authorBenazza, Hussain
date accessioned2023-08-16T18:36:15Z
date available2023-08-16T18:36:15Z
date copyright4/3/2023 12:00:00 AM
date issued2023
identifier issn2642-6641
identifier otherjesbc_4_1_011004.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292199
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.
publisherThe American Society of Mechanical Engineers (ASME)
titleMoroccan Consumer Energy Consumption Itemsets and Inter-Appliance Associations Using Machine Learning Algorithms and Data Mining Techniques
typeJournal Paper
journal volume4
journal issue1
journal titleASME Journal of Engineering for Sustainable Buildings and Cities
identifier doi10.1115/1.4062113
journal fristpage11004-1
journal lastpage11004-10
page10
treeASME Journal of Engineering for Sustainable Buildings and Cities:;2023:;volume( 004 ):;issue: 001
contenttypeFulltext


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