id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
easat-5716	Babikou, Yéloiti N’poh ; Guenoukpati, Agbassou ; Salami, Adekunlé Akim ; Kodjo, Koffi Mawugno 	Hybrid approach based on wavelets, Kalman filters, Arima, and neural networks for mastering electrical energy at the residential level: Forecasting the electrical energy consumption of residences in the city of Lomé	2025	16	.pdf	application/pdf	6771	312	48	Additionally, the availability of a database containing residential electrical energy data is essential for analyzing, understanding, and modeling residential energy consumption Materials and Methods For this study, residential electrical energy data was collected every minute for 28 houses from a dataset gathered in Lomé, southern Togo, West Africa, covering the period from 15/07/2021 10:15 to 28/12/2023 23:59 for all 28 residences considered.	cache/easat-5716.pdf	txt/easat-5716.txt