Brillouin scattering spectrum character extraction based on genetic algorithm and seeker optimization algorithm

• Published in: 高技术通讯（英文版） Vol. 25; no. 4; pp. 401 - 407
• Main Authors: Zhang Yanjun, Jin Peijun, Fu Xinghu, Hou Jiaoru, Zhang Fangcao, Xu Jinrui
• Format: Journal Article
• Language: English
• Published: Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, Missouri 65401, USA%The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province, School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, P.R.China 01.12.2019; The Key Laboratory for Special Fiber and Fiber Sensor of Hebei Province, School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, P.R.China
• Subjects: seeker optimization algorithm ( SOA); Brillouin scattering spectrum ( BSS); Brillouin frequency shift ( BFS); particle swarm optimization ( PSO); ge-netic algorithm ( GA)
• ISSN: 1006-6748
• DOI: 10.3772/j.issn.1006-6748.2019.04.008

A new hybrid optimization method based on genetic algorithm ( GA) and seeker optimization al-gorithm ( SOA) is presented in this paper.The hybrid algorithm optimizes SOA by using crossover and mutation operations in GA in order to improve the global search ability of SOA.Four algorithms, i.e.particle swarm optimization ( PSO) , SOA, GA and quantum-behaved particle swarm optimiza-tion ( GA-QPSO) and GA-SOA are used to process the simulation and experimental data of Brillouin scattering spectrum ( BSS) at different temperatures.The results show that GA-SOA improves the accuracy of extracting the center frequency shift and the minimum center frequency of Brillouin scat-tering spectrum compared with other three algorithms.The shift error is 0.203 MHz.Therefore, GA-SOA can be applied to the accurate extraction of BSS characteristics.