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Non-Destructive Spectroscopy Assisted by Machine Learning for Coal Industrial Analysis: Recent Advances and Future Perspectives

https://doi.org/10.2139/ssrn.5020324

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Qualitative Discrimination Analysis of Coals Based on Their Laser-Induced Breakdown Spectra

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Application of Multivariate Linear Regression for Determination of Ash Content in Coal by XRF Analysis

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Elemental and proximate analysis of coal by x-ray fluorescence assisted laser-induced breakdown spectroscopy

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inferredcites →https://doi.org/10.1177/0003702818772856openalex-snapshot

Development of a Rapid Coal Analyzer Using Laser-Induced Breakdown Spectroscopy (LIBS)

inferredcites →https://doi.org/10.1186/s40537-021-00444-8openalex-snapshot

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

inferredcites →https://doi.org/10.12438/cst.2023-1778openalex-snapshot

Research progress and application of online coal quality and coal quantity analyses

inferredcites →https://doi.org/10.1364/ao.394746openalex-snapshot

Accuracy improvement of quantitative LIBS analysis of coal properties using a hybrid model based on a wavelet threshold de-noising and feature selection method

inferredcites →https://doi.org/10.1364/oe.405438openalex-snapshot

Recognition of coal from other minerals in powder form using terahertz spectroscopy

inferredcites →https://doi.org/10.1366/0003702021954232openalex-snapshot

Development and Commercial Evaluation of Laser-Induced Breakdown Spectroscopy Chemical Analysis Technology in the Coal Power Generation Industry

inferredcites →https://doi.org/10.1366/000370209788964458openalex-snapshot

Design of a Laser-Induced Breakdown Spectroscopy System for On-Line Quality Analysis of Pulverized Coal in Power Plants

inferredcites →https://doi.org/10.1366/0003702854248836openalex-snapshot

Near-Infrared Diffuse Reflectance Spectroscopy of Coal

inferredcites →https://doi.org/10.1366/10-06190openalex-snapshot

Extracting Coal Ash Content from Laser-Induced Breakdown Spectroscopy (LIBS) Spectra by Multivariate Analysis

inferredcites →https://doi.org/10.1366/11-06393openalex-snapshot

A Nonlinearized Multivariate Dominant Factor–Based Partial Least Squares (PLS) Model for Coal Analysis by Using Laser-Induced Breakdown Spectroscopy

inferredcites →https://doi.org/10.1366/13-07345openalex-snapshot

Application of a Spectrum Standardization Method for Carbon Analysis in Coal Using Laser-Induced Breakdown Spectroscopy (LIBS)

inferredcites →https://doi.org/10.2991/eame-15.2015.131openalex-snapshot

Application of Infrared Spectroscopy in the Detection of Coal Quality of Power Plant

inferredcites →https://doi.org/10.31897/pmi.2022.89openalex-snapshot

Rapid detection of coal ash based on machine learning and X-ray fluorescence

inferredcites →https://doi.org/10.3390/app11199274openalex-snapshot

Review of Element Analysis of Industrial Materials by In-Line Laser—Induced Breakdown Spectroscopy (LIBS)

inferredcites →https://doi.org/10.3390/app13010006openalex-snapshot

Determination of Calorific Value of Mixed Coals by Analysis of Major Elements Using Data Pre-Processing in Laser-Induced Breakdown Spectroscopy

inferredcites →https://doi.org/10.3390/app13148158openalex-snapshot

Rapid Classification and Quantification of Coal by Using Laser-Induced Breakdown Spectroscopy and Machine Learning

inferredcites →https://doi.org/10.3390/app131810049openalex-snapshot

Quantitative Analysis of Coal Quality by a Portable Laser Induced Breakdown Spectroscopy and Three Chemometrics Methods

inferredcites →https://doi.org/10.3390/app14020593openalex-snapshot

Coal–Rock Data Recognition Method Based on Spectral Dimension Transform and CBAM-VIT

inferredcites →https://doi.org/10.3390/app14041431openalex-snapshot

Research on the Application of THz-TDS in Coal–Rock Interface Recognition

inferredcites →https://doi.org/10.3390/app14041606openalex-snapshot

Application of Semi-Supervised Learning Model to Coal Sample Classification

inferredcites →https://doi.org/10.3390/app9224868openalex-snapshot

A Novel Artificial Intelligence Technique to Estimate the Gross Calorific Value of Coal Based on Meta-Heuristic and Support Vector Regression Algorithms

inferredcites →https://doi.org/10.3390/chemosensors10110490openalex-snapshot

Detection of Carbon Content from Pulverized Coal Using LIBS Coupled with DSC-PLS Method

inferredcites →https://doi.org/10.3390/chemosensors11070363openalex-snapshot

Coal Calorific Value Detection Technology Based on NIRS-XRF Fusion Spectroscopy

inferredcites →https://doi.org/10.3390/pr9020316openalex-snapshot

Machine Learning-Based Prediction of Selected Parameters of Commercial Biomass Pellets Using Line Scan Near Infrared-Hyperspectral Image

inferredcites →https://doi.org/10.4028/www.scientific.net/amm.483.71openalex-snapshot

DWT-SVM on Near-Infrared Spectra for Moisture and Volatile Determination of Coal

inferredcites →https://doi.org/10.4028/www.scientific.net/amm.556-562.575openalex-snapshot

Quantitative Analysis and Research to Coal Quality Based on Near Infrared Spectrum

inferredcites →https://doi.org/10.4028/www.scientific.net/amm.80-81.279openalex-snapshot

PLS Regression on Coal Infrared Spectrum with Wavelet Pre-Processing

inferredcites →https://doi.org/10.4028/www.scientific.net/amr.236-238.799openalex-snapshot

Fourier Transform Near Infrared Spectroscopy Analysis of Power Plant Coal Quality

inferredcites →https://doi.org/10.4028/www.scientific.net/amr.898.831openalex-snapshot

Pre-Processing Influence on Near-Infrared Spectra for Determination of Volatile in Lignite Coal Samples

inferredcites →https://doi.org/10.5513/jcea01/16.1.1535openalex-snapshot

Recent applications of vibrational mid-Infrared (IR) spectroscopy for studying soil components: a review

inferredcites →https://doi.org/10.56530/spectroscopy.uw8474c3openalex-snapshot

Automatic Coal-Rock Recognition by Laser-Induced Breakdown Spectroscopy Combined with an Artificial Neural Network

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