Banca de QUALIFICAÇÃO: DAVI GUIMARÃES DA SILVA

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : DAVI GUIMARÃES DA SILVA
DATE: 09/09/2022
TIME: 08:30
LOCAL: Laboratório de Inteligência Computacional / Plataforma Jitsi
TITLE:

Forecasting of Electric Power Consumption Time Series with Deep Learning for an IoT System 

KEY WORDS:

Deep Learning. Internet of things. Energy efficiency. Deep Neural Networks. Prediction module

PAGES: 72
BIG AREA: Outra
AREA: Ciências Ambientais
SUMMARY:

Energy consumption and energy efficiency are topics that have attracted the attention of researchers in recent years, in order to seek in order to seek scientific and technological solutions for energy production and reduction of costs. One of the alternatives that have obtained satisfactory results is the use of technologies based on Internet of Things (IoT) and Deep Learning systems. Based on this, we assessed the performance of Long Short-Term Memory (LSTM) neural networks in time series electric energy consumption prediction, for a forecasting module of an IoT system. Three time series were used and we compared LSTM to the algorithms Extreme Boost Gradient and Random Forest. Computational results indicate that the LSTM model showed a tendency of better RMSE performance in the first data set, and statistically significant better results in other two data sets, according to the Kruskal-Wallis test (p < 0.0001 in both cases). Thus, the proposed model was implemented and validated from experiments, presenting accurate prediction for monitoring and estimating power consumption, being applicable to Energy Efficiency and decision making.

BANKING MEMBERS:
Presidente - 1963026 - ANDERSON ALVARENGA DE MOURA MENESES
Externa ao Programa - 2143011 - HELAINE CRISTINA MORAES FURTADO
Externo à Instituição - ROBERTO SCHIRRU - UFRJ
Externa à Instituição - ANDRESSA DOS SANTOS NICOLAU - UFRJ