Photoacoustic discrimination of blood based on BP-PSO algorithm combined with improved dynamic inertia weight strategy function

Zhong Ren; Tao Liu; Chengxin Xiong; Wenping Peng; Junli Wu

doi:10.1117/12.2626668

15 November 2022 Photoacoustic discrimination of blood based on BP-PSO algorithm combined with improved dynamic inertia weight strategy function

Zhong Ren, Tao Liu, Chengxin Xiong, Wenping Peng, Junli Wu

Author Affiliations +

Proceedings Volume 12448, 5th Optics Young Scientist Summit (OYSS 2022); 124481P (2022) https://doi.org/10.1117/12.2626668
Event: 5th Optics Young Scientist Summit (OYSS 2022), 2022, Fuzhou, China

Abstract

In this work, we used photoacoustic spectroscopy to distinguish the different types of blood including four kinds of true blood and two kinds of fake blood. The peak-to-peak spectra of blood were obtained in the wavelength from 700nm to 1064nm based on the established photoacoustic detection system of blood. To accurately discriminate the different types of blood, back propagation (BP) neural network was used to train the photoacoustic peak-to-peak spectra of training blood with 120 groups, the correct rate of distinguishing blood is 76.7% for 30 groups of test samples. Particle swarm optimization (PSO) algorithm was used to optimize the parameters of BP network. The effects of neurons number in the hidden layer, learning rate factor, inertia weight, two acceleration factors, iteration times and training times on the corret rate and mean square error were all investigated. Under the optimal parameters, the correct rate of BP-PSO algorithm was increased to 93.3%. To further improve the correct rate, the dynamic inertia weight strategy was used. Moreover, a kind of improved dynamic inertia weight strategy function was proposed. The correct rate of the improved dynamic inertia weight strategy function was compared with that of the static inertia weight and two other dynamic inertia weight strategy functions. Under the optimal value of the improved dynamic inertia weight, the correct rate reached 96.7%. Therefore, the BP-PSO algorithm combined with the improved dynamic inertia weight strategy function has a potential value in the photoacoustic discrimination of blood.

Citation Download Citation

Zhong Ren, Tao Liu, Chengxin Xiong, Wenping Peng, and Junli Wu "Photoacoustic discrimination of blood based on BP-PSO algorithm combined with improved dynamic inertia weight strategy function", Proc. SPIE 12448, 5th Optics Young Scientist Summit (OYSS 2022), 124481P (15 November 2022); https://doi.org/10.1117/12.2626668

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