Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Everton Jose Santana"'
Publikováno v:
Information, Vol 12, Iss 10, p 394 (2021)
With data collected by Internet of Things sensors, deep learning (DL) models can forecast the generation capacity of photovoltaic (PV) power plants. This functionality is especially relevant for PV power operators and users as PV plants exhibit irreg
Externí odkaz:
https://doaj.org/article/8dcd3143098d45b395eba3a506ddb04b
Autor:
Francois Haddad, Xiao Li, Dalia Perelman, Everton Jose Santana, Tatiana Kuznetsova, Nicholas Cauwenberghs, Vincent Busque, Kevin Contrepois, Michael P. Snyder, Mary B. Leonard, Christopher Gardner
Publikováno v:
Clinical Nutrition ESPEN. 53:43-52
Background & Aims: Resting energy expenditure (REE) is a major component of energy balance. While REE is usually indexed to total body weight (TBW), this may introduce biases when assessing REE in obesity or during weight loss intervention. The main
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e397a35d7b890c6950182aedefaaaf7
https://doi.org/10.1016/j.clnesp.2022.11.015
https://doi.org/10.1016/j.clnesp.2022.11.015
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Choosing the most suitable algorithm to perform a machine learning task for a new problem is a recurrent and complex task. In multi-target regression tasks , when problem transformation methods are applied, this choice is even harder. The reason is t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8fb9e529464ba22ad56cff28ae7ec198
https://hdl.handle.net/11368/3014623
https://hdl.handle.net/11368/3014623
Publikováno v:
Information, Vol 12, Iss 394, p 394 (2021)
Information
Volume 12
Issue 10
Information
Volume 12
Issue 10
With data collected by Internet of Things sensors, deep learning (DL) models can forecast the generation capacity of photovoltaic (PV) power plants. This functionality is especially relevant for PV power operators and users as PV plants exhibit irreg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e054783959c77e3ac230dd344ba9003d
https://hdl.handle.net/11368/3037244
https://hdl.handle.net/11368/3037244
Autor:
Sylvio Barbon, Everton Jose Santana, Felipe Rodrigues dos Santos, Saulo Martiello Mastelini, Fábio Luiz Melquiades
Publikováno v:
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Universidade de São Paulo (USP)
instacron:USP
Machine Learning (ML) algorithms have been used for assessing soil quality parameters along with non-destructive methodologies. Among spectroscopic analytical methodologies, energy dispersive X-ray fluorescence (EDXRF) is one of the more quick, envir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9630bda7247d3a7a98faca99a959b099
http://arxiv.org/abs/2002.04312
http://arxiv.org/abs/2002.04312
Several applications of supervised learning involve the prediction of multiple continuous target variables from a dataset. When the target variables exhibit statistical dependencies among them, a multi-target regression (MTR) modelling permits to imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6100836ff04cfcc08de00181171fda77
https://hdl.handle.net/11368/3014645
https://hdl.handle.net/11368/3014645
Autor:
Jessica Fernandes Lopes, Everton Jose Santana, Bruno Bogaz Zarpelão, Victor G. Turrisi da Costa, Sylvio Barbon Junior
Edge computing (EC) is a promising technology capable of bridging the gap between Cloud computing services and the demands of emerging technologies such as the Internet of Things (IoT). Most EC-based solutions, from wearable devices to smart cities a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e6bffca90dc4290e96c13a070c839e7d
https://hdl.handle.net/11368/3014641
https://hdl.handle.net/11368/3014641
Autor:
Douglas Fernandes Barbin, Sylvio Barbon Junior, Everton Jose Santana, Nuria Aleixos Borrás, Amanda Teixeira Badaró
Publikováno v:
Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis ISBN: 9789811564949
Spectral methods usually produce a large amount of data, and have been greatly applied to food and agricultural products. These products demand several analyses to determine different parameters, that will further indicate their quality. There have b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85d421b9562fde6f1bbc6fbc3f1c56e2
https://doi.org/10.1007/978-981-15-6495-6_5
https://doi.org/10.1007/978-981-15-6495-6_5
Publikováno v:
Intelligent Systems ISBN: 9783030613792
BRACIS (2)
BRACIS (2)
Forecasting photovoltaic (PV) power generation, as in many other time series scenarios, is a challenging task. Most current solutions for time series forecasting are grounded on Machine Learning (ML) algorithms, which usually outperform statistical-b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ceb3eb1e561891ba7aa75415985f1e3
https://link.springer.com/chapter/10.1007/978-3-030-61380-8_43
https://link.springer.com/chapter/10.1007/978-3-030-61380-8_43
Publikováno v:
Green, Pervasive, and Cloud Computing ISBN: 9783030192228
GPC
GPC
Machine Learning (ML) solutions need to deal efficiently with a huge amount of data available, addressing scalability concerns without sacrificing predictive performance. Moreover, this data comes in the form of a continuous and evolving stream impos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b37bec5c6c2d1b18ed448d6fc1f7962
https://doi.org/10.1007/978-3-030-19223-5_1
https://doi.org/10.1007/978-3-030-19223-5_1