Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Francisco Elânio Bezerra"'
Autor:
Francisco Elânio Bezerra, Geraldo Cardoso de Oliveira Neto, Gabriel Magalhães Cervi, Rafaella Francesconi Mazetto, Aline Mariane de Faria, Marcos Vido, Gustavo Araujo Lima, Sidnei Alves de Araújo, Mauro Sampaio, Marlene Amorim
Publikováno v:
Applied Sciences, Vol 14, Iss 8, p 3337 (2024)
In the context of Industry 4.0, managing large amounts of data is essential to ensure informed decision-making in intelligent production environments. It enables, for example, predictive maintenance, which is essential for anticipating and identifyin
Externí odkaz:
https://doaj.org/article/5fd61b182d48404c9a1d29bd3c7a09dc
Publikováno v:
International Journal of Energy Sector Management. 16:1172-1191
Purpose This paper aims to propose an approach based upon the principal component analysis (PCA) to define a contribution rate for each variable and then select the main variables as inputs to a neural network for energy load forecasting in the regio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7552b9776218115ebcde0355cc77f937
https://doi.org/10.1108/ijesm-12-2019-0009
https://doi.org/10.1108/ijesm-12-2019-0009
Autor:
Fabio Henrique Pereira, Francisco Elânio Bezerra, Diego Oliva, Gilberto Francisco Martha de Souza, Ivan Eduardo Chabu, Josemir Coelho Santos, Shigueru Nagao Junior, Silvio Ikuyo Nabeta
Publikováno v:
Sensors, Vol 20, Iss 24, p 7242 (2020)
The prediction of partial discharges in hydrogenerators depends on data collected by sensors and prediction models based on artificial intelligence. However, forecasting models are trained with a set of historical data that is not automatically updat
Externí odkaz:
https://doaj.org/article/f763596646204fa1b04addd58c3076e0
Autor:
Francisco Elânio Bezerra, Fernando André Zemuner Garcia, Silvio Ikuyo Nabeta, Gilberto Francisco Martha de Souza, Ivan Eduardo Chabu, Josemir Coelho Santos, Shigueru Nagao Junior, Fabio Henrique Pereira
Publikováno v:
Sensors, Vol 20, Iss 9, p 2730 (2020)
Dissolved gas analysis (DGA) is one of the most important methods to analyze fault in power transformers. In general, DGA is applied in monitoring systems based upon an autoregressive model; the current value of a time series is regressed on past val
Externí odkaz:
https://doaj.org/article/8b07d9d76b954c74a5fd7b48c6e05919
Publikováno v:
Engineering review. 41:65-75
In Brazil, the electric power distributors must buy electricity on auctions one, three and five years ahead. If there is inefficiency in the contracting of electric energy, the chamber of Commercialization of Electric Energy, which enables the commer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6974e6d376ab9d2665c34b155355e5e
https://doi.org/10.30765/er.1529
https://doi.org/10.30765/er.1529
Autor:
Fabio Henrique Pereira, Francisco Elânio Bezerra, Shigueru Junior, Josemir Santos, Ivan Chabu, Gilberto Francisco Martha de Souza, Fábio Micerino, Silvio Ikuyo Nabeta
Publikováno v:
Energies, Vol 11, Iss 7, p 1691 (2018)
Transformers are one of the most important part in a power system and, especially in key-facilities, they should be closely and continuously monitored. In this context, methods based on the dissolved gas ratios allow to associate values of gas concen
Externí odkaz:
https://doaj.org/article/43cf82fd9043448680eb6269e4e6451c
Autor:
Diego Oliva, Fabio Henrique Pereira, Gilberto Francisco Martha de Souza, Francisco Elânio Bezerra, Ivan Eduardo Chabu, Josemir Coelho Santos, Shigueru Nagao Junior, Silvio Ikuyo Nabeta
Publikováno v:
Sensors, Vol 20, Iss 7242, p 7242 (2020)
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 24
Sensors (Basel, Switzerland)
Sensors
Volume 20
Issue 24
The prediction of partial discharges in hydrogenerators depends on data collected by sensors and prediction models based on artificial intelligence. However, forecasting models are trained with a set of historical data that is not automatically updat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e3ff45199cd134bdaf37bcbd90e65de
https://www.mdpi.com/1424-8220/20/24/7242
https://www.mdpi.com/1424-8220/20/24/7242
Autor:
Gilberto Francisco Martha de Souza, Silvio Ikuyo Nabeta, Fabio Henrique Pereira, Francisco Elânio Bezerra, Fernando André Zemuner Garcia, Ivan Eduardo Chabu, Shigueru Nagao Junior, Josemir Coelho Santos
Publikováno v:
Sensors
Volume 20
Issue 9
Sensors, Vol 20, Iss 2730, p 2730 (2020)
Sensors (Basel, Switzerland)
Volume 20
Issue 9
Sensors, Vol 20, Iss 2730, p 2730 (2020)
Sensors (Basel, Switzerland)
Dissolved gas analysis (DGA) is one of the most important methods to analyze fault in power transformers. In general, DGA is applied in monitoring systems based upon an autoregressive model
the current value of a time series is regressed on past
the current value of a time series is regressed on past
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05838f8de3f5f1daa64b59af150b1a98
Publikováno v:
Computer Methods and Programs in Biomedicine. 205:106078
Background and objective an accurate estimation of the epidemiological model coefficients helps understand the basic principles of disease spreading. Some studies showed that dozens of hours are needed to simulate the traditional probabilistic cellul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9a32366d4891e08217b7f4ef835959b
https://doi.org/10.1016/j.cmpb.2021.106078
https://doi.org/10.1016/j.cmpb.2021.106078
Autor:
Gilberto Francisco Martha de Souza, Francisco Elânio Bezerra, Silvio Ikuyo Nabeta, Josemir Coelho Santos, Ivan Eduardo Chabu, Fabio Jose Micerino, Shigueru Nagao Junior, Fabio Henrique Pereira
Publikováno v:
Energies, Vol 11, Iss 7, p 1691 (2018)
Energies; Volume 11; Issue 7; Pages: 1691
Energies; Volume 11; Issue 7; Pages: 1691
Transformers are one of the most important part in a power system and, especially in key-facilities, they should be closely and continuously monitored. In this context, methods based on the dissolved gas ratios allow to associate values of gas concen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc2e942f02218297d22574349a534ba5
https://doi.org/10.3390/en11071691
https://doi.org/10.3390/en11071691