Chinese Journal of Lasers, Volume. 45, Issue 4, 404001(2018)
Estimation of Atmospheric Optical Turbulence at Near Surface of Chengdu with Support Vector Machine
Figures & Tables(6)
Fig. 3. Measurement and estimation results of Cn2 in Chengdu with SVM model and W71 algorithm
Fig. 4. Frequency number distribution histogram and cumulative probability distribution of lgCn2 from 2014-05-13 to 2014-05-18. (a) SVM model; (b) W71 algorithm
Fig. 5. Scatter plots of estimated and measured values of Cn2 with different methods. (a) W71 algorithm (06:00—18:00); (b) W71 algorithm (from 18:00 to 06:00 of following day); (c) SVM model ( 06:00—18:00); (d) SVM algorithm (from 18:00 to 06:00 of following day)
Table 1. Performance parameters of three-dimensionalultrasonic anemometer CSAT3, temperature humiditysensor HMP 155, and micro-thermal sensor
View tableTable 1. Performance parameters of three-dimensionalultrasonic anemometer CSAT3, temperature humiditysensor HMP 155, and micro-thermal sensor
Instrument name Measuring parameter Output range Offset error Resolution Ux /m·s-1±30 ±0.8 0.01 Uy /m·s-1±30 ±0.8 0.01 CSAT3 Uz /m·s-1±8 ±0.4 0.005 /m-2/3 5×10-16 RH /% 0.8-100 ±1 0.1 HMP 155 Temperature /℃ -80-60 ±1.7 Micro- thermal sensor /m-2/3 10-12-10-18 3×10-18
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Lü Jie, Zhu Wenyue, Qing Chun, Wu Xiaoqing, Chen Shasha. Estimation of Atmospheric Optical Turbulence at Near Surface of Chengdu with Support Vector Machine[J]. Chinese Journal of Lasers, 2018, 45(4): 404001
Paper Information
Category: Measurement and metrology
Received: Aug. 29, 2017
Accepted: --
Published Online: Apr. 13, 2018
The Author Email: Wenyue Zhu (zhuwenyue@aiofm.ac.cn)
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