Firefly as a novel swarm intelligence variable selection method in spectroscopy

Mohammad Goodarzi, Leandro dos Santos Coelho

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle.This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models.The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same.

Original languageEnglish (US)
Pages (from-to)20-27
Number of pages8
JournalAnalytica Chimica Acta
Volume852
DOIs
StatePublished - Jan 1 2014

Fingerprint

Fireflies
Least-Squares Analysis
Intelligence
Spectrum Analysis
spectroscopy
Spectroscopy
Feature extraction
Calibration
Wavelength
wavelength
prediction
Insects
calibration
Particle swarm optimization (PSO)
Food
Animals
genetic algorithm
Genetic algorithms
nest
Swarm intelligence

Keywords

  • Chemometrics
  • Firefly algorithm
  • Spectroscopy
  • Variable selection

ASJC Scopus subject areas

  • Analytical Chemistry
  • Environmental Chemistry
  • Biochemistry
  • Spectroscopy

Cite this

Firefly as a novel swarm intelligence variable selection method in spectroscopy. / Goodarzi, Mohammad; dos Santos Coelho, Leandro.

In: Analytica Chimica Acta, Vol. 852, 01.01.2014, p. 20-27.

Research output: Contribution to journalArticle

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