Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Vector support machine"'
Publikováno v:
Journal of Materials Research and Technology, Vol 15, Iss , Pp 1562-1571 (2021)
In the present work, the use of the support vector machine (SVM) algorithm is proposed to generate models that allow predicting the geometrical accuracy of molds manufactured via single point incremental forming (SPIF) using aluminized steel sheets D
Externí odkaz:
https://doaj.org/article/d0dfbb7cd20a4238a311326b4085e1ab
Publikováno v:
Energies, Vol 14, Iss 8, p 2332 (2021)
Different prediction models (multiple linear regression, vector support machines, artificial neural networks and random forests) are applied to model the monthly global irradiation (MGI) from different input variables (latitude, longitude and altitud
Externí odkaz:
https://doaj.org/article/9e56f0106e7d4d419685854019c932ac
Autor:
Gilberto Rivera, Rogelio Florencia, Vicente García, Alejandro Ruiz, J. Patricia Sánchez-Solís
Publikováno v:
Applied Sciences, Vol 10, Iss 18, p 6253 (2020)
‘El Diario de Juárez’ is a local newspaper in a city of 1.5 million Spanish-speaking inhabitants that publishes texts of which citizens read them on both a website and an RSS (Really Simple Syndication) service. This research applies natural-lan
Externí odkaz:
https://doaj.org/article/f3f313641e3743579ddcbe659a15e874
Akademický článek
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Publikováno v:
Indonesian Journal of Electrical Engineering and Computer Science. 28:98
We describe the design and development of sensor nodes, based on Edge computing technologies, for the processing and classification of events detected in physiological signals such as the electrocardiographic signal (ECG is the electrical signal of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da7781977c5162d78407455e1cdb89c3
https://doi.org/10.11591/ijeecs.v28.i1.pp98-105
https://doi.org/10.11591/ijeecs.v28.i1.pp98-105
Autor:
Gayatri A. Deochake, Vilas S. Gaikwad
Coronavirus (COVID-19) is spreading rapidly around the world and, as of October 2020, more than 1,966,000 people have been infected in more than 200 countries. Early detection of COVID-19 is essential for the provision and protection of HIV-negative
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a87134bab14e1ad905363dcb847524fc
https://zenodo.org/record/5509828
https://zenodo.org/record/5509828
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
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Quadratic vector support machine algorithm, applied to prediction of university student satisfaction
Autor:
Omar Chamorro-Atalaya, Guillermo Morales-Romero, Yeferzon Meza-Chaupis, Elizabeth Auqui-Ramos, Jesús Ramos-Cruz, César León-Velarde, Irma Aybar-Bellido
Publikováno v:
Indonesian Journal of Electrical Engineering and Computer Science. 27:139
This study aims to identify the most optimal supervised learning algorithm to be applied to the prediction of satisfaction of university students. In this study, the IBM SPSS - 25.0 software was used to test the reliability of the satisfaction questi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6baa59308159099286525e9673cfc6f5
https://doi.org/10.11591/ijeecs.v27.i1.pp139-148
https://doi.org/10.11591/ijeecs.v27.i1.pp139-148
Publikováno v:
Investigo. Repositorio Institucional de la Universidade de Vigo
Universidade de Vigo (UVigo)
Energies, Vol 14, Iss 2332, p 2332 (2021)
Energies
Volume 14
Issue 8
Universidade de Vigo (UVigo)
Energies, Vol 14, Iss 2332, p 2332 (2021)
Energies
Volume 14
Issue 8
Different prediction models (multiple linear regression, vector support machines, artificial neural networks and random forests) are applied to model the monthly global irradiation (MGI) from different input variables (latitude, longitude and altitud
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6620b09f187bca9af546940ae742b965
https://www.mdpi.com/1996-1073/14/8/2332
https://www.mdpi.com/1996-1073/14/8/2332
Publikováno v:
Journal of Materials Research and Technology 15, 1562-1571 (2021)
Helvia. Repositorio Institucional de la Universidad de Córdoba
instname
Journal of Materials Research and Technology, Vol 15, Iss, Pp 1562-1571 (2021)
Helvia. Repositorio Institucional de la Universidad de Córdoba
instname
Journal of Materials Research and Technology, Vol 15, Iss, Pp 1562-1571 (2021)
In the present work, the use of the support vector machine (SVM) algorithm is proposed to generate models that allow predicting the geometrical accuracy of molds manufactured via single point incremental forming (SPIF) using aluminized steel sheets D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::348955aaad053406b25498eefb4d9db4
http://hdl.handle.net/10396/22043
http://hdl.handle.net/10396/22043