contributor author | Abassi, Abdelfattah | |
contributor author | Arid, Ahmed | |
contributor author | Benazza, Hussain | |
date accessioned | 2023-08-16T18:36:15Z | |
date available | 2023-08-16T18:36:15Z | |
date copyright | 4/3/2023 12:00:00 AM | |
date issued | 2023 | |
identifier issn | 2642-6641 | |
identifier other | jesbc_4_1_011004.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4292199 | |
description abstract | The 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. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Moroccan Consumer Energy Consumption Itemsets and Inter-Appliance Associations Using Machine Learning Algorithms and Data Mining Techniques | |
type | Journal Paper | |
journal volume | 4 | |
journal issue | 1 | |
journal title | ASME Journal of Engineering for Sustainable Buildings and Cities | |
identifier doi | 10.1115/1.4062113 | |
journal fristpage | 11004-1 | |
journal lastpage | 11004-10 | |
page | 10 | |
tree | ASME Journal of Engineering for Sustainable Buildings and Cities:;2023:;volume( 004 ):;issue: 001 | |
contenttype | Fulltext | |