Optical fiber network abnormal data detection algorithm based on deep learning

Yunpeng Liu; Xiaoli Huo; Zhichao Liu

doi:10.3788/IRLA20210029

Journals >Infrared and Laser Engineering >Volume 50 >Issue 6 >Page 20210029 > Article

Infrared and Laser Engineering
Vol. 50, Issue 6, 20210029 (2021)

Optical fiber network abnormal data detection algorithm based on deep learning

Yunpeng Liu¹, Xiaoli Huo¹, and Zhichao Liu^2、*

Author Affiliations

¹College of Information Engineering, Jiaozuo University, Jiaozuo 454000, China

²School of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China

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DOI: 10.3788/IRLA20210029 Cite this Article

Yunpeng Liu, Xiaoli Huo, Zhichao Liu. Optical fiber network abnormal data detection algorithm based on deep learning[J]. Infrared and Laser Engineering, 2021, 50(6): 20210029 Copy Citation Text

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Fig. 1. Flow chart of DL-GA algorithm

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Fig. 2. Comparison of the stability of the three algorithms

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Fig. 3. Convergence time of the three algorithms for different data sets

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Test time/s	Actual abnormal data	Test abnormal data
		GA		CA		DL-GA
		Test value	Relative error	Test value	Relative error	Test value	Relative error
5	106	131	0.236	135	0.274	113	0.066
10	168	193	0.149	199	0.185	178	0.059
15	214	245	0.145	236	0.103	203	0.051
20	259	283	0.088	279	0.077	268	0.035
25	384	422	0.093	424	0.104	395	0.029
30	410	448	0.094	451	0.101	421	0.028
35	467	510	0.092	512	0.098	480	0.029
40	515	562	0.093	565	0.097	531	0.031
45	539	590	0.095	594	0.102	553	0.027
50	621	679	0.094	681	0.098	639	0.029

Table 1. Statistical table of test abnormal data volume and actual abnormal data volume

Yunpeng Liu, Xiaoli Huo, Zhichao Liu. Optical fiber network abnormal data detection algorithm based on deep learning[J]. Infrared and Laser Engineering, 2021, 50(6): 20210029

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