Variables selection methods in near-infrared spectroscopy
Near-infrared (NIR) spectroscopy has increasingly been adopted as an analytical tool in
various fields, such as the petrochemical, pharmaceutical, environmental, clinical …
various fields, such as the petrochemical, pharmaceutical, environmental, clinical …
Decision support and intelligent systems in the textile and apparel supply chain: An academic review of research articles
This article provides a comprehensive review of research articles related to the application
of decision support and intelligent systems in the textile and apparel supply chains. Data …
of decision support and intelligent systems in the textile and apparel supply chains. Data …
Effect of variable selection algorithms on model performance for predicting moisture content in biological materials using spectral data
Variable selection is a critical step for designing a dedicated multispectral real-time system
from multicollinearity spectral data. It improves the prediction ability of the calibration model …
from multicollinearity spectral data. It improves the prediction ability of the calibration model …
Determination of total volatile basic nitrogen (TVB-N) content and Warner–Bratzler shear force (WBSF) in pork using Fourier transform near infrared (FT-NIR) …
J Cai, Q Chen, X Wan, J Zhao - Food Chemistry, 2011 - Elsevier
Total volatile basic nitrogen (TVB-N) content is one of important index of pork's freshness,
and Warner–Bratzler shear force (WBSF) is seen as the important index of pork's …
and Warner–Bratzler shear force (WBSF) is seen as the important index of pork's …
Long-term evaluation of soluble solids content of apples with biological variability by using near-infrared spectroscopy and calibration transfer method
The long-term performance of a near-infrared (NIR) calibration model for soluble solids
content (SSC) prediction has been investigated using apples with biological variability …
content (SSC) prediction has been investigated using apples with biological variability …
Estimation of soil organic matter content using selected spectral subset of hyperspectral data
W Sun, S Liu, X Zhang, Y Li - Geoderma, 2022 - Elsevier
Soil organic matter (SOM) content plays an important role in the global carbon cycle and
agricultural activities. Reflectance spectroscopy has been recognized as a promising …
agricultural activities. Reflectance spectroscopy has been recognized as a promising …
Evaluation of machine learning approaches to predict soil organic matter and pH using Vis-NIR spectra
Soil organic matter (SOM) and pH are essential soil fertility indictors of paddy soil in the
middle-lower Yangtze Plain. Rapid, non-destructive and accurate determination of SOM and …
middle-lower Yangtze Plain. Rapid, non-destructive and accurate determination of SOM and …
[HTML][HTML] Performance and optimisation study of waste plastic aggregate based sustainable concrete–A machine learning approach
abstract The use of waste plastic made aggregates in cement concrete not only can solve
the problem of the disposal of waste plastics in a sustainable way but also it reduces the …
the problem of the disposal of waste plastics in a sustainable way but also it reduces the …
Combining the genetic algorithm and successive projection algorithm for the selection of feature wavelengths to evaluate exudative characteristics in frozen–thawed …
The potential use of feature wavelengths for predicting drip loss in grass carp fish, as
affected by being frozen at− 20° C for 24 h and thawed at 4° C for 1, 2, 4, and 6 days, was …
affected by being frozen at− 20° C for 24 h and thawed at 4° C for 1, 2, 4, and 6 days, was …
Prediction of dissolved oxygen concentration in hypoxic river systems using support vector machine: a case study of Wen-Rui Tang River, China
X Ji, X Shang, RA Dahlgren, M Zhang - Environmental Science and …, 2017 - Springer
Accurate quantification of dissolved oxygen (DO) is critically important for managing water
resources and controlling pollution. Artificial intelligence (AI) models have been successfully …
resources and controlling pollution. Artificial intelligence (AI) models have been successfully …