Banca de DEFESA: NATASSIA RAFAELLE MEDEIROS SIQUEIRA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : NATASSIA RAFAELLE MEDEIROS SIQUEIRA
DATE: 25/02/2023
TIME: 10:00
LOCAL: remoto
TITLE:

The use of machine learning to classify electricity consumption profiles in different regions of Brazil

KEY WORDS:

Machine Learning; Transfer Learning; energy forecasting

PAGES: 67
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SPECIALTY: Sistemas de Informação
SUMMARY:

Accurate forecasting of energy consumption can significantly contribute to improving distribution management and 

potentially contribute to controlling and reducing energy consumption rates. Advances in data-based computational

 techniques are becoming increasingly robust and popular as they achieve good accuracy in results. This study 

proposes the development of a model capable of classifying energy consumption profiles in the residential sector, 

using machine learning and transfer learning techniques. The application of Machine Learning (MA) techniques in 

energy production can indicate great potential for controlling and managing the production and distribution of 

electric energy, which can bring greater efficiency, improve production and optimize distribution. In this study, we 

combine AM techniques with the transfer of learning that is able to use pre-established knowledge in new contexts 

(knowledge bases), making the energy forecasting process more efficient and robust.

COMMITTEE MEMBERS:
Presidente - 1350250 - ANNE MAGALY DE PAULA CANUTO
Interno - 2177445 - BRUNO MOTTA DE CARVALHO
Externo à Instituição - DIEGO SILVEIRA COSTA NASCIMENTO - IFRN