Stacking Ensemble Learning Algorithm Based Rapid Inverse Modelling of Copper Grade Using Imaging Spectral Data DOI
Jingli Wang,

Jingxiang Gao

Published: Jan. 1, 2024

Language: Английский

One-dimensional convolutional neural networks with infrared spectroscopy for classifying the origin of printing paper DOI Creative Commons
Sung‐Wook Hwang,

Geungyong Park,

Jinho Kim

et al.

BioResources, Journal Year: 2024, Volume and Issue: 19(1), P. 1633 - 1651

Published: Jan. 24, 2024

Herein, the challenge of accurately classifying manufacturing origin printing paper, including continent, country, and specific product, was addressed. One-dimensional convolutional neural network (1D CNN) models trained on infrared (IR) spectrum data acquired from paper samples were used for task. The preprocessing IR spectra through a second-derivative transformation restriction spectral range to 1800 1200 cm-1 improved classification performance model. outcomes highly promising. Models in 1200-cm-1 exhibited perfect continent with an impressive F1 score 0.980 product classification. Notably, developed 1D CNN model outperformed traditional machine learning classifiers, such as support vector machines feed-forward networks. In addition, application point attribution enhanced transparency decision-making process model, offering insights into patterns that affect This study makes considerable contribution classification, potential implications accurate identification various fields.

Language: Английский

Citations

10
Random Forest Regressor for Predicting Sensory Texture of Emotional Designed Packaging Films DOI Creative Commons
Yong Ju Lee,

Min Jung Joo,

Ha Kyoung Yu

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: 25, P. 104147 - 104147

Published: Jan. 23, 2025

Language: Английский

Citations

1
Recent developments in the use of machine learning in catalysis: A broad perspective with applications in kinetics DOI Creative Commons
Leandro Goulart de Araujo, Léa Vilcocq, Pascal Fongarland

et al.

Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 160872 - 160872

Published: Feb. 1, 2025

Language: Английский

Citations

1
Interpretability in near-infrared (NIR) spectroscopy: Current pathways to the long-standing challenge DOI Creative Commons
Krzysztof B. Beć, Justyna Grabska, Christian W. Huck

et al.

TrAC Trends in Analytical Chemistry, Journal Year: 2025, Volume and Issue: 189, P. 118254 - 118254

Published: April 14, 2025

Language: Английский

Citations

1
Development of a Data-Driven Framework to Predict Waste Generation and Evaluate Influential Factors: Machine Learning Innovations in Construction Waste Management DOI Creative Commons

Sahar Ghorbani,

Siavash Ghorbany, Esmatullah Noorzai

et al.

Cleaner Waste Systems, Journal Year: 2025, Volume and Issue: unknown, P. 100299 - 100299

Published: April 1, 2025

Language: Английский

Citations

1
Evaluating the performance of machine learning and variable selection methods to identify document paper using infrared spectral data DOI
Yong Ju Lee,

Soon Wan Kweon,

Chang Woo Jeong

et al.

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Journal Year: 2024, Volume and Issue: 327, P. 125299 - 125299

Published: Oct. 18, 2024

Language: Английский

Citations

4
Methods for Estimating Resting Energy Expenditure in Intensive Care Patients: A comparative study of Predictive Equations with Machine Learning and Deep Learning Approaches DOI Creative Commons
Christopher Yew Shuen Ang, Mohd Basri Mat Nor, Nurdiana Nordin

et al.

Computer Methods and Programs in Biomedicine, Journal Year: 2025, Volume and Issue: 262, P. 108657 - 108657

Published: Feb. 9, 2025

Language: Английский

Citations

0
A tree-based machine learning surrogate model for predicting off-axis tensile mechanical properties of 2.5D woven composites at high temperatures DOI
Chao Zhang, Zeyu Bian, Tinh Quoc Bui

et al.

Composite Structures, Journal Year: 2025, Volume and Issue: unknown, P. 119044 - 119044

Published: March 1, 2025

Language: Английский

Citations

0
The effects of feedstock types and their properties on hydrothermal carbonisation and resulting hydrochar: A review DOI Creative Commons
Vigneshwaran Shanmugam, Elif Kaynak, Oisik Das

et al.

Current Opinion in Green and Sustainable Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 101024 - 101024

Published: March 1, 2025

Language: Английский

Citations

0
Cellulose I Crystallinity Estimation Using a Combination of Infrared Spectroscopy and Machine Learning Approaches DOI
Yong Ju Lee, Do Young Lee,

Tai-Ju Lee

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0