Research on Raman fiber amplifier using neural network combining PSO algorithm
Pages 89 - 95
Abstract
We propose an efficient hybrid method that combines neural network and particle swarm optimization algorithm to optimize the performance of backward multi-pumped Raman fiber amplifiers. We use a neural network to inverse system design Raman fiber amplifier by learning the nonlinear mapping relationship between pump light and the output gain. To obtain a flat gain spectrum, the particle swarm optimization algorithm is used to search for the optimal pump slight parameter configuration. The results show that when the designed Raman amplifier is oriented toward C+L band signal optical amplification, the error between the target gain value and the actual gain value is less than 0.47 dB, the output gain after optimization is 17.96dB, and the gain flatness is 0.44dB.
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- Research on Raman fiber amplifier using neural network combining PSO algorithm
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Published In
September 2022
1221 pages
ISBN:9781450396899
DOI:10.1145/3573942
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Published: 16 May 2023
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AIPR 2022
AIPR 2022: 2022 5th International Conference on Artificial Intelligence and Pattern Recognition
September 23 - 25, 2022
Xiamen, China
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