نتایج جستجو برای: 103 than plsr method rmse0167
تعداد نتایج: 3266060 فیلتر نتایج به سال:
Over the years development of selective estrogen receptor (ER) ligands has been of great concern to researchers involved in the chemistry and pharmacology of anticancer drugs, resulting in numerous synthesized selective ER subtype inhibitors. In this work, a data set of 82 ER ligands with ERα and ERβ inhibitory activities was built, and quantitative structure-activity relationship (QSAR) method...
The monitoring of soil salinity levels is necessary for the prevention and mitigation of land degradation in arid environments. To assess the potential of remote sensing in estimating and mapping soil salinity in the El-Tina Plain, Sinai, Egypt, two predictive models were constructed based on the measured soil electrical conductivity (ECe) and laboratory soil reflectance spectra resampled to La...
Rapid and non-destructive prediction of mango sweetness and acidity using near infrared spectroscopy
The study aimed on evaluating the feasibility of NIRS to predict sweetness and acidity of intact mango fruit in form of soluble solids content (SSC) and titratable acidity (TA) through calibration modeling. Diffuse reflectance spectra in NIR wavelength range of 1000 – 2500 nm were acquired for a total of 58 mango samples. PCR and PLSR were used to develop SCC or TA prediction models respectivel...
Spectroscopy has proven to be an efficient tool for measuring the properties of meat. In this article, hyperspectral imaging (HSI) techniques are used to determine the moisture content in cooked chicken breast over the VIS/NIR (400-1,000 nm) spectral range. Moisture measurements were performed using an oven drying method. A partial least squares regression (PLSR) model was developed to extract ...
Near-infrared spectroscopy (NIRS), a rapid and efficient tool, was used to determine the total amount of nine ginsenosides in Panax ginseng. In the study, the regression models were established using multivariate regression methods with the results from conventional chemical analytical methods as reference values. The multivariate regression methods, partial least squares regression (PLSR) and ...
Soil organic matter (SOM) plays an important role in the field of climate change and terrestrial ecosystems. SOM large areas, especially urban is difficult to monitor estimate by traditional methods. Urban land structure complex, soil a mixture inorganic constituents with different physical chemical properties. Previous studies showed that remote sensing techniques provide diverse data visible-...
Online near-infrared spectroscopy was used as a process analysis technique in the synthesis of 2-chloropropionate for the first time. Then, the partial least squares regression (PLSR) quantitative model of the product solution concentration was established and optimized. Correlation coefficient (R (2)) of partial least squares regression (PLSR) calibration model was 0.9944, and the root mean sq...
Partial least squares regression (PLSR) has been a popular technique to explore the linear relationship between two datasets. However, most of algorithm implementations of PLSR may only achieve a suboptimal solution through an optimization on the Euclidean space. In this paper, we propose several novel PLSR models on Riemannian manifolds and develop optimization algorithms based on Riemannian g...
To optimize plant architecture (e.g., photosynthetic active leaf area, leaf-stem ratio), plant physiologists and plant breeders rely on destructively and tediously harvested biomass samples. A fast and non-destructive method for obtaining information about different plant organs could be vehicle-based spectral proximal sensing. In this 3-year study, the mobile phenotyping platform PhenoTrac 4 w...
This paper investigates the use of Local Linear Embedded Regression (LLER) for the quantitative analysis of glucose from near infrared spectra. The performance of the LLER model is evaluated and compared with the regression techniques Principal Component Regression (PCR), Partial Least Squares Regression (PLSR) and Support Vector Regression (SVR) both with and without pre-processing. The predic...
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