Acta Optica Sinica, Vol. 40, Issue 24, 2401002 (2020)
Estimation of Surface Layer Optical Turbulence Using Artificial Neural Network
Chen Xiaowei1,2, Zhu Wenyue1,2,*, Qian Xianmei1,2,**, Luo Tao1,2, Sun Gang1,2, Liu Qing1,2, Li Xuebin1,2, and Weng Ningquan1,2
- 1Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics,Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui 230031, China
- 2Anhui Laboratory of Advanced Laser Technology, Hefei, Anhui 230037, China
This paper presents an estimate of surface layer optical turbulence in Northwest China using an artificial neural network. We optimize the configuration of the multilayer perceptron (MLP), including 10 features in the input layer and 40 neurons in the hidden layer. The performance of the constructed MLP is investigated. The results show that when the training set and testing set are from the same site, the mean relative error of the model is 1.34%. The goodness of fit between measured and estimated refractive index structure constants is 0.94. We propose that when the training set and testing set come from different sites, the generalization ability of the MLP should be enhanced.
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