LED Spectrum Matching Based on Equilibrium Optimizer Algorithm
Since its proposal,the Equilibrium Optimizer algorithm has attracted much attention from scholars at home and abroad,and its application areas have been extensively studied.This paper proposes to use the Equilibrium Optimizer algorithm as a spectrum matching algorithm for matching the spectra of low blue light LED health products.The spectrum of low blue light LED health products from the American company Sorra was selected as the target spectrum for fitting.The Gaussian model was used to characterize the distribution of monochromatic LEDs,and the Equilibrium Optimizer algorithm was utilized to obtain the optimal proportion coefficients of the monochromatic LEDs,thereby achieving spectrum reproduction.The simulated spectrum reproduced closely matches the target spectrum,with a Pearson correlation coefficient of 0.9777.Furthermore,a comparison was made with the classical Genetic Algorithm and Particle Swarm Optimization Algorithm,using Pearson correlation coefficient and coefficient of determination R2 as evaluation criteria.The results show that compared to Genetic Algorithm and Particle Swarm Optimization Algorithm,the Equilibrium Optimizer algorithm has the advantages of fast operation speed,high efficiency,and small fitting errors in matching with the target spectrum.
LEDspectrum matchingequilibrium optimizer algorithmcurve fittinglow blue light
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