Gebruikersprofielen voor Roberto Zanetti Freire
Roberto Z. FreireUniversidade Tecnológica Federal do Paraná (UTFPR) Geverifieerd e-mailadres voor utfpr.edu.br Geciteerd door 1808 |
[HTML][HTML] Hybrid-YOLO for classification of insulators defects in transmission lines based on UAV
Transmission power lines are essential to supply electrical energy to consumption centers.
Keeping a reliable transmission system requires the early identification of faults. Image-…
Keeping a reliable transmission system requires the early identification of faults. Image-…
[HTML][HTML] Optimized hybrid ensemble learning approaches applied to very short-term load forecasting
The significance of accurate short-term load forecasting (STLF) for modern power systems’
efficient and secure operation is paramount. This task is intricate due to cyclicity, non-…
efficient and secure operation is paramount. This task is intricate due to cyclicity, non-…
Fault detection in insulators based on ultrasonic signal processing using a hybrid deep learning technique
S Frizzo Stefenon, R Zanetti Freire… - IET Science …, 2020 - Wiley Online Library
Identifying problems in insulators is a task that requires the experience of the operator.
Contaminated insulators generally do not represent a system failure, however, due to higher …
Contaminated insulators generally do not represent a system failure, however, due to higher …
Electrical insulator fault forecasting based on a wavelet neuro-fuzzy system
S Frizzo Stefenon, R Zanetti Freire… - Energies, 2020 - mdpi.com
The surface contamination of electrical insulators can increase the electrical conductivity of
these components, which may lead to faults in the electrical power system. During inspections…
these components, which may lead to faults in the electrical power system. During inspections…
Optimized hybrid YOLOu‐Quasi‐ProtoPNet for insulators classification
To ensure the electrical power supply, inspections are frequently performed in the power grid.
Nowadays, several inspections are conducted considering the use of aerial images since …
Nowadays, several inspections are conducted considering the use of aerial images since …
Photovoltaic power forecasting using wavelet neuro-fuzzy for active solar trackers
SF Stefenon, C Kasburg, RZ Freire… - Journal of Intelligent …, 2021 - content.iospress.com
The generation of electric energy by photovoltaic (PV) panels depends on many parameters,
one of them is the sun’s angle of incidence. By using solar active trackers, it is possible to …
one of them is the sun’s angle of incidence. By using solar active trackers, it is possible to …
Agribusiness time series forecasting using Wavelet neural networks and metaheuristic optimization: An analysis of the soybean sack price and perishable products …
Brazilian agribusiness is responsible for almost 25% of the country gross domestic product,
and companies from this economic sector may have strategies to control their actions in a …
and companies from this economic sector may have strategies to control their actions in a …
Optimized ensemble extreme learning machine for classification of electrical insulators conditions
The classification of distinct problems of insulators in the distribution networks is a task that
requires operator's experience. The applications of techniques to automate the inspection of …
requires operator's experience. The applications of techniques to automate the inspection of …
Capacitive effect on the heat transfer through building glazing systems
In recent years, several intensive studies have been carried out in order to reduce the
energy consumption of buildings. One solution lies on whole building energy simulation that …
energy consumption of buildings. One solution lies on whole building energy simulation that …
Population's variance-based adaptive differential evolution for real parameter optimization
Differential evolution (DE) is an evolutionary algorithm (EA) that uses a rather greedy and
less stochastic approach to solve optimization problems than other evolutionary methods [1]. …
less stochastic approach to solve optimization problems than other evolutionary methods [1]. …