THE OPTIMAL WAVELENGTHS FOR LIGHT ABSORPTION SPECTROSCOPY MEASUREMENTS BASED ON GENETIC ALGORITHM-PARTICLE SWARM OPTIMIZATION
Abstract
To select the optimal wavelengths in the light extinction spectroscopy measurement, genetic algorithm-particle swarm optimization (GAPSO) based on genetic algorithm (GA) and particle swarm optimization (PSO) is adopted. The change of the optimal wavelength positions in different feature size parameters and distribution parameters is evaluated. Moreover, the Monte Carlo method based on random probability is used to identify the number of optimal wavelengths, and good inversion effects of the particle size distribution are obtained. The method proved to have the advantage of resisting noise. In order to verify the feasibility of the algorithm, spectra with bands ranging from 200 to 1000 nm are computed. Based on this, the measured data of standard particles are used to verify the algorithm.
Keywords
обнаружение частиц в воде,
спектроскопия поглощения,
распределение размеров частиц,
оптимальная длина волны,
генетический алгоритм,
оптимизация роя частиц,
water particles detection,
light extinction spectroscopy,
particle size distribution,
optimal wavelength,
particle swarm genetic hybrid optimization algorithm
About the Authors
G. . Tang
Chongqing University
Russian Federation
Russian Federation
B. . Wei
Chongqing University
Russian Federation
Russian Federation
D. . Wu
Chongqing University; Chongqing Industry Polytechnic College
Russian Federation
Russian Federation
P. . Feng
Chongqing University
Russian Federation
Russian Federation
J. . Liu
Chongqing University
Russian Federation
Russian Federation
Y. . Tang
Chongqing University
Russian Federation
Russian Federation
Sh. . Xiong
Chongqing University
Russian Federation
Russian Federation
Z. . Zhang
Chongqing University
Russian Federation
Russian Federation
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Review
For citations:
Tang G., Wei B., Wu D., Feng P., Liu J., Tang Y., Xiong Sh., Zhang Z. THE OPTIMAL WAVELENGTHS FOR LIGHT ABSORPTION SPECTROSCOPY MEASUREMENTS BASED ON GENETIC ALGORITHM-PARTICLE SWARM OPTIMIZATION. Zhurnal Prikladnoii Spektroskopii. 2018;85(1):119-128. (In Russ.)
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