Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Ciza A. Mushagalusa"'
Publikováno v:
Onderstepoort Journal of Veterinary Research, Vol 88, Iss 1, Pp e1-e10 (2021)
The article reviews the outbreaks and distribution of African swine fever (ASF) in South Africa since the first probable outbreak that occurred in the Koedoesrand Ward in 1926. Retrospective data on the ASF outbreaks in South Africa were obtained fro
Externí odkaz:
https://doaj.org/article/4cae58d715d541f9babfc5e696e030a0
Random forest and spatial cross-validation performance in predicting species abundance distributions
Publikováno v:
Environmental Systems Research, Vol 13, Iss 1, Pp 1-24 (2024)
Abstract Random forests (RF) have been widely used to predict spatial variables. Several studies have shown that spatial cross-validation (CV) methods consistently cause RF to yield larger prediction errors compared to standard CV methods. This study
Externí odkaz:
https://doaj.org/article/1e52181264fe4ddfac4cf48ece298713
Publikováno v:
Journal of Probability and Statistics.
Machine learning algorithms, especially random forests (RFs), have become an integrated part of the modern scientific methodology and represent an efficient alternative to conventional parametric algorithms. This study aimed to assess the influence o
Autor:
Ciza Arsène Mushagalusa, Lucilla Steinaa, Bisimwa Basengere, Michel M. Dione, Juliette R. Ongus, Patrick N. Bisimwa
Publikováno v:
Journal of Veterinary Science
Background African swine fever (ASF) is an infectious viral disease of domestic pigs that presents as a hemorrhagic fever, and for which no effective vaccine is available. The disease has a serious negative social and economic impact on pig keepers.
Akademický článek
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Autor:
Baudouin Michel, Katcho Karume, Ciza Arsène Mushagalusa, Yannick Mugumaarhahama, Elvis Tshibasu, Jan Bogaert, Eric Lutete, Nadège Cirezi Cizungu, Raymond Lumbuenamo, Deckas Ganza
Publikováno v:
Trees, Forests and People, Vol 5, Iss, Pp 100104-(2021)
This paper analyzes active fires from 2001 to 2019 in and around the Luki Biosphere Reserve, western DR Congo to assess fire risks. In this study, we used descriptive statistics to assess fire events, Getis-Ord G hotspot analysis to define the spatia
Autor:
Baenyi Simon, Patrick, Owino Joseph, Junga, Ochieng, Joel Winyo, Tiambo, Christian Keambou, Tarekegn, Getinet Mekuriaw, Machuka, Eunice M., Kabange, Dorine, Musale, Katunga, Ciza, Arsène Mushagalusa, Kizungu, Roger Vumilia, Pelle, Roger
Publikováno v:
Journal of Applied Animal Research; Dec 2021, Vol. 49 Issue 1, p423-430, 8p
Publikováno v:
Journal of Probability and Statistics, Vol 2022 (2022)
Machine learning algorithms, especially random forests (RFs), have become an integrated part of the modern scientific methodology and represent an efficient alternative to conventional parametric algorithms. This study aimed to assess the influence o
Externí odkaz:
https://doaj.org/article/d91b1f1616f14261b26a03e6765e81b6
Autor:
Nadège Cirezi Cizungu, Elvis Tshibasu, Eric Lutete, Ciza Arsène Mushagalusa, Yannick Mugumaarhahama, Deckas Ganza, Katcho Karume, Baudouin Michel, Raymond Lumbuenamo, Jan Bogaert
Publikováno v:
Trees, Forests and People, Vol 5, Iss , Pp 100104- (2021)
This paper analyzes active fires from 2001 to 2019 in and around the Luki Biosphere Reserve, western DR Congo to assess fire risks. In this study, we used descriptive statistics to assess fire events, Getis-Ord G hotspot analysis to define the spatia
Externí odkaz:
https://doaj.org/article/be919fe02aef44ea819f9eb194efdc14