Resultados de búsqueda - Random variables.

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  1. Marriage between variable selection and prediction methods to model plant disease risk por Suarez, Franco, Bruno, Cecilia, Kurina Giannini, Franca, Gimenez, Maria, Rodriguez Pardina, Patricia, Balzarini, Mónica Graciela

    Publicado 2023
    “…The disease risk predictors were constructed with a logistic linear regression model (LR) and the random forest (RF) algorithm, using all the available variables and the subgroups of variables selected by each feature selection method. …”
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    Artículo
  2. Analyzing inflow to Faye reservoir sensitivity to climate change using CMIP6 and random forest algorithm por Akaffou, F. H., Obahoundje, Salomon, Didi, S. R. M., Koffi, B., Coulibaly, W. B., Habel, M., Kadjo, M. M. F., Kouassi, K. L., Diedhiou, A.

    Publicado 2024
    “…In the era of Climate Change and Climate Variability (CC and CV), renewable energy sources such as Hydropower (HP) have a significant role to play in mitigation. …”
    Enlace del recurso
    Journal Article
  3. Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy por Silva, ‪João Vasco, Heerwaarden, Joost van, Reidsma, Pytrik, Laborte, Alice G., Tesfaye, Kindie, Ittersum, Martin K. van

    Publicado 2023
    “…Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. …”
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    Journal Article
  4. Classification of ground lichen using Sentinel-2 and airborne laser data por Larsson, Helene

    Publicado 2018
    “…Classifcation of lichen coverage was carried out with the Random Forest algorithm, and 90 field plots were used as training data. …”
    H3
  5. Genetic diversity in cowpea as revealed by random amplified polymorphic DNA por Mignouna, Hodeba D., Ng, N.Q., Ikea, J., Thottappilly, G.

    Publicado 1998
    “…In this study, random amplified polymorphic DNA (RAPD) markers were used to assess genetic diversity in cowpea (Vigna unguiculata (L). …”
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    Journal Article
  6. Comparative evaluation of the contributions of soil physicochemical properties to variations in the yields of four major staple food crops in eastern Nigeria por Asadu, C., Dixon, A., Okechukwu, R.

    Publicado 2002
    “…The data were from three replicates of two randomized complete block design experiments sited in a newly cleared forest and on previously cultivated land both in Nsukka, eastern Nigeria. …”
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    Journal Article
  7. Short range spatial variability of soil physico-chemical variables related to earthworm clustering in a Neotropical gallery forest por Jiménez, J.J., Decaëns, Thibaud, Amézquita Collazos, Edgar, Rao, Idupulapati M., Thomas, Richard J., Lavelle, Patrick M.

    Publicado 2011
    “…Partial Mantel test revealed specific significant relationships between soil variables and some species. The earthworm community of the GF displayed a random structure in a spatially clumped soil environment, and our results suggested that spatial distribution observed for some species could be the result of preferential selection of soil environmental factors. …”
    Enlace del recurso
    Journal Article
  8. From rangelands to cropland, land-use change and its impact on soil organic carbon variables in a Peruvian Andean highlands: a machine learning modeling approach por Carbajal, Mariella, Ramirez, David A., Turin Canchaya, Cecilia Claudia, Schaeffer, Sean M., Konkel, Julie, Ninanya, Johan, Rinza, Javier, De Mendiburu, Felipe, Zorogastua, Percy, Villaorduña, Liliana, Quiroz, Roberto

    Publicado 2024
    “…A total of 198 soil samples (0.3 m depth) were collected to assess SOC variables. Four ML algorithms—random forest (RF), support vector machine (SVM), artificial neural networks (ANNs), and eXtreme gradient boosting (XGB)—were used to model SOC variablesusing remote sensing data, land-use and landcover (LULC, nine categories), climate topography, and sampled physical–chemical soil variables. …”
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    Artículo
  9. Climate variability and change: perceptions, experiences and realities por Rao, K.P.C., Oyoo A

    Publicado 2012
    “…While the role and significance of some of these factors on productivity and profitability can be perceived more easily due to their relative predictability, extreme variability in climate and the random nature of that variability makes it difficult for farmers to accurately perceive trends in climate. …”
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    Capítulo de libro
  10. A model of labeling with horizontal differentiation and cost variability por Saak, Alexander E.

    Publicado 2011
    “…We study optimal disclosure of variety by a multiproduct firm with random costs. The prices for labeled varieties are increasing functions of the cost differential and do not reveal which variety is cheaper to produce. …”
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    Journal Article
  11. A model of labeling with horizontal differentiation and cost variability por Saak, Alexander E.

    Publicado 2011
    “…We study optimal disclosure of variety by a multi-product firm with random costs. In our model there are two varieties that are horizontally differentiated and differ in overall quality, but buyers cannot distinguish between them without labels. …”
    Enlace del recurso
    Artículo preliminar
  12. Genetic variability and evolutionary dynamics of viruses of the family Closteroviridae. por Rubio, Luis, Guerri, José, Moreno, Pedro

    Publicado 2017
    “…Here we performed an updated analysis of sequences available in Genbank and reviewed present knowledge on the genetic variability and evolutionary processes of viruses of the family Closteroviridae. …”
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    Artículo
  13. Spatial and Temporal Variability of Transplanted Rice At the Field Scale por Dobermann, Achim, Pampolino, Mirasol F., Neue, Heinz-Ulrich

    Publicado 1995
    “…At all growth stages, two samples of three randomly selected hills were sufficient to measure plant height in a field. …”
    Enlace del recurso
    Journal Article

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