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Updated: May 16, 2025

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Variational mode decomposition unfolded extreme learning machine for spectral quantitative analysis of complex

Liangliang Shen1, Jiajing Zhao2, Deyun Wu1

  • 1School of Chemical Engineering and Technology, Tiangong University, Tianjin 300387, PR China.

Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
|May 14, 2025
PubMed
Summary

A new VMD-UELM model combines variational mode decomposition (VMD) and extreme learning machine (ELM) for accurate spectral quantitative analysis. This approach efficiently analyzes complex samples like blood and fuel oil.

Keywords:
Ensemble modelingExtreme learning machineMultivariate calibrationVariational mode decomposition

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Area of Science:

  • Analytical Chemistry
  • Chemometrics
  • Machine Learning

Background:

  • Spectral quantitative analysis is crucial for complex sample characterization.
  • Traditional methods may face challenges with intricate spectral data.
  • Variational Mode Decomposition (VMD) and Extreme Learning Machine (ELM) offer advanced decomposition and modeling capabilities.

Purpose of the Study:

  • To introduce a novel regression model, Variational Mode Decomposition Unfolded Extreme Learning Machine (VMD-UELM), for enhanced spectral quantitative analysis.
  • To integrate the strengths of VMD for signal decomposition and ELM for data modeling.

Main Methods:

  • Spectra are decomposed into mode components (uk) using VMD.
  • These mode components are then unfolded into an extended matrix.
  • A quantitative model is established by applying ELM to the unfolded matrix and target values.

Main Results:

  • The VMD-UELM model's efficiency was validated on datasets of hemoglobin, aromatics, and Panax notoginseng (PN).
  • Performance was evaluated using blood, fuel oil, and adulterated herb samples.
  • VMD-UELM demonstrated comparable or superior performance against established methods like Partial Least Squares (PLS) and standalone ELM.

Conclusions:

  • VMD-UELM is an effective and efficient approach for the spectral quantitative analysis of complex samples.
  • The hybrid VMD-ELM strategy provides a robust framework for chemometric modeling.
  • This method holds promise for applications requiring precise spectral data interpretation.