نتایج جستجو برای: telar forests
تعداد نتایج: 39425 فیلتر نتایج به سال:
Random forests are a type of ensemble method which makes predictions by combining the results of several independent trees. However, the theory of random forests has long been outpaced by their application. In this paper, we propose a novel random forests algorithm based on cooperative game theory. Banzhaf power index is employed to evaluate the power of each feature by traversing possible feat...
In Northern Europe the use of tree biomass for production of energy is mostly based on thinning of forests, harvest residues, stumps from final cutting, bark of commercial roundwood, and organic waste of pulp industry. Results based on field experiments allow estimations of 137Cs activity removed from forests in wood fuel, and also the activity returned in ash used as a fertiliser. After one fe...
Scene-context plays an important role in scene analysis and object recognition. Among various sources of scene-context, we focus on scene-context scale, which means the effective scale of local context to classify an image pixel in a scene. This paper presents random forests based image categorization using the scene-context scale. The proposed method uses random forests, which are ensembles of...
Tropical rain forests play a dominant role in global biosphere-atmosphere CO(2) exchange. Although climate and nutrient availability regulate net primary production (NPP) and decomposition in all terrestrial ecosystems, the nature and extent of such controls in tropical forests remain poorly resolved. We conducted a meta-analysis of carbon-nutrient-climate relationships in 113 sites across the ...
Random forests (RF) is a popular general purpose classifier that has been shown to outperform many other classifiers on a variety of datasets. The widespread use of random forests can be attributed to several factors, some of which include its excellent empirical performance, scale and unit invariance, robustness to outliers, time and space complexity, and interpretability. While RF has many de...
Having accurate quantitative and qualitative information about the state of forest stands, is necessary for any basic management and planning, to reduce the effects of forest degradation. The current study aimed to model the destruction of Hyrcanian forests under the effects of density and volume (per hectare) variables, using logistic regression. In total, 252 plots of 1000 m2 area were measur...
The biophysical effects of forests on climate have been extensively studied with climate models. However, models cannot accurately reproduce local climate effects due to their coarse spatial resolution and uncertainties, and field observations are valuable but often insufficient due to their limited coverage. Here we present new evidence acquired from global satellite data to analyse the biophy...
The intermediate disturbance hypothesis (IDH) predicts local species diversity to be maximal at an intermediate level of disturbance. Developed to explain species maintenance and diversity patterns in species-rich ecosystems such as tropical forests, tests of IDH in tropical forest remain scarce, small-scale and contentious. We use an unprecedented large-scale dataset (2504 one-hectare plots an...
Maximum height was assessed for tree species from seven temperate deciduous forests, one subtropical forest and one tropical forest and combined with published tree heights for three other tropical forests. The temperate deciduous forests showed a strong concentration of canopy species and a dearth of subcanopy species. In contrast, the four tropical forests showed more uniform distributions of...
Random forests have emerged as one of the most commonly used nonparametric statistical methods in many scientific areas, particularly in analysis of high throughput genomic data. A general practice in using random forests is to generate a sufficiently large number of trees, although it is subjective as to how large is sufficient. Furthermore, random forests are viewed as "black-box" because of ...
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