Variables selection methods in near-infrared spectroscopy

Z Xiaobo, Z Jiewen, MJW Povey, M Holmes… - Analytica chimica …, 2010 - Elsevier
Near-infrared (NIR) spectroscopy has increasingly been adopted as an analytical tool in
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

EWT Ngai, S Peng, P Alexander, KKL Moon - Expert Systems with …, 2014 - Elsevier
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 …

Effect of variable selection algorithms on model performance for predicting moisture content in biological materials using spectral data

M Kamruzzaman, D Kalita, MT Ahmed, G ElMasry… - Analytica Chimica …, 2022 - Elsevier
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 …

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 …

Long-term evaluation of soluble solids content of apples with biological variability by using near-infrared spectroscopy and calibration transfer method

S Fan, J Li, Y Xia, X Tian, Z Guo, W Huang - Postharvest Biology and …, 2019 - Elsevier
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 …

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 …

Evaluation of machine learning approaches to predict soil organic matter and pH using Vis-NIR spectra

M Yang, D Xu, S Chen, H Li, Z Shi - Sensors, 2019 - mdpi.com
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 …

[HTML][HTML] Performance and optimisation study of waste plastic aggregate based sustainable concrete–A machine learning approach

A Shiuly, T Hazra, D Sau, D Maji - Cleaner Waste Systems, 2022 - Elsevier
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 …

Combining the genetic algorithm and successive projection algorithm for the selection of feature wavelengths to evaluate exudative characteristics in frozen–thawed …

JH Cheng, DW Sun, H Pu - Food chemistry, 2016 - Elsevier
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 …

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 …