نتایج جستجو برای: plsr method has high performance rmse0142
تعداد نتایج: 5673764 فیلتر نتایج به سال:
Soil organic matter (SOM) is a key index of soil fertility. Visible and near-infrared (VNIR, 350–2500 nm) reflectance spectroscopy an effective method for modeling SOM content. Characteristic wavelength screening spectral transformation may improve the performance prediction. This study aimed to explore optimal combination characteristic selection hyperspectral SOM. A total 219 topsoil (0–20 cm...
Recently, there has been an increased attention in the literature on the use of ensemble methods in multivariate regression and classification. These methods have been shown to have interesting properties both for regression and classification. In particular, they can improve the accuracy of unstable predictors. Ensemble methods have so far, been little studied in situations that are common for...
Effective pretreatment of spectral reflectance is vital to model accuracy in soil parameter estimation. However, the classic integer derivative has some disadvantages, including spectral information loss and the introduction of high-frequency noise. In this paper, the fractional order derivative algorithm was applied to the pretreatment and partial least squares regression (PLSR) was used to as...
BACKGROUND Decision making in patients with low flow-low gradient aortic stenosis mainly depends on the actual stenosis severity and left ventricular function, which is of prognostic importance. We used 2-dimensional strain parameters measured by speckle tracking at rest and during dobutamine stress echocardiography to document the extent of myocardial impairment, its relationship with hemodyna...
The use of spectral features to estimate leaf area index (LAI) is generally considered a challenging task for hyperspectral data. In this study, the hyperspectral reflectance of winter wheat was selected to optimize the selection of spectral features and to evaluate their performance in modeling LAI at various growth stages during 2008 and 2009. We extracted hyperspectral features using differe...
Near-infrared spectroscopy (NIRS) was implemented to monitor the moisture content of broadleaf litters. Partial least-squares regression (PLSR) models, incorporating optimal wavelength selection techniques, have been proposed to better predict the litter moisture of forest floor. Three broadleaf litters were used to sample the reflection spectra corresponding the different degrees of litter moi...
testing plays a vital role in any language teaching program. it allows teachers and stakeholders, including program administrators, parents, admissions officers and prospective employers to be assured that the learners are progressing according to an accepted standard (douglas, 2010). the problems currently facing language testers have both practical and theoretical implications but the first i...
In situ measurements with visible and near-infrared spectroscopy (vis-NIR) provide an efficient way for acquiring soil information of paddy soils in the short time gap between the harvest and following rotation. The aim of this study was to evaluate its feasibility to predict a series of soil properties including organic matter (OM), organic carbon (OC), total nitrogen (TN), available nitrogen ...
The characterization of plant nutrients is important to understand the process of plant growth in natural ecosystems. This study attempted to evaluate the performances of univariate linear regression with various vegetation indices (VIs) and multivariate regression methods in estimating grass nutrients (i.e., nitrogen (N) and phosphorus (P)) with canopy hyperspectral reflectance. Synthetically ...
Although crop-growth monitoring is important for agricultural managers, it has always been a difficult research topic. However, unmanned aerial vehicles (UAVs) equipped with RGB and hyperspectral cameras can now acquire high-resolution remote-sensing images, which facilitates accelerates such monitoring. To explore the effect of single indicator multiple indicators, this study combines six grow...
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