Vis-NIR spectrometric determination of Brix and sucrose in sugar production samples using kernel partial least squares with interval selection based on the successive projections algorithm
نویسندگان
چکیده
منابع مشابه
Determination of Protein and Moisture in Fishmeal by Near-Infrared Reflectance Spectroscopy and Multivariate Regression Based on Partial Least Squares
The potential of Near Infrared Reflectance Spectroscopy (NIRS) as a fast method to predict the Crude Protein (CP) and Moisture (M) content in fishmeal by scanning spectra between 1000 and 2500 nm using multivariate regression technique based on Partial Least Squares (PLS) was evaluated. The coefficient of determination in calibration (R2C) and Standard Error of Calibra...
متن کاملLearning-based super resolution using kernel partial least squares
a r t i c l e i n f o In this paper, we propose a learning-based super resolution approach consisting of two steps. The first step uses the kernel partial least squares (KPLS) method to implement the regression between the low-resolution (LR) and high-resolution (HR) images in the training set. With the built KPLS regression model, a primitive super-resolved image can be obtained. However, this...
متن کاملSimultaneous spectrophotometric determination of lead, copper and nickel using xylenol orange by partial least squares
A partial least squares (PLS) calibration model was developed for the simultaneous spectrophotometricdetermination of Pb (ΙΙ), Cu (ΙΙ) and Ni (ΙΙ) using xylenol orange as a chromogenic reagent. The parameterscontrolling behavior of the system were investigated and optimum conditions were selected. The calibrationgraphs were linear in the ranges of 0.0–9.091, 0.0–2.719 and 0.0–2.381 ppm for lead...
متن کاملMulti-Kernel Partial Least Squares Regression Modeling based on Adaptive Genetic Algorithm
Kernel learning based soft sensor model has been focus of the machine learning domain. Kernel partial least squares (KPLS) algorithm can construct nonlinear models using the extract latent variables from the input and output data space simultaneously. However, the generalization of KPLS model relies on the model’s kernel type and kernel parameter for different modeling data. Thus, linear combin...
متن کاملKernel Partial Least Squares for Stationary Data
We consider the kernel partial least squares algorithm for non-parametric regression with stationary dependent data. Probabilistic convergence rates of the kernel partial least squares estimator to the true regression function are established under a source and an effective dimensionality condition. It is shown both theoretically and in simulations that long range dependence results in slower c...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Talanta
سال: 2018
ISSN: 0039-9140
DOI: 10.1016/j.talanta.2017.12.064