International Journal of Frontiers in Engineering Technology, 2021, 3(1); doi: 10.25236/IJFET.2021.030101.
Weibing Feng, Licheng Jiang* and Danya Liang
College of Science, Xi'an University of Science and Technology, Xi'an 710000, China
*Corresponding author
Studying the correlation between various meteorological elements and visibility is of great significance to the establishment of visibility prediction methods. This paper first uses a quadratic linear polynomial model to fit the relationship between visibility and seven meteorological factors, and uses Matlab's stepwise regression function to solve the problem. Finally, the relationship expression between visibility and various meteorological factors is obtained. And the expression can be better The forecast dominates the trend of visibility.
Visibility, Meteorological Factors, Polynomial Fitting
Weibing Feng, Licheng Jiang, Danya Liang. Research on Forecast of Airport Visibility Based on Multivariate Statistics. International Journal of Frontiers in Engineering Technology (2021), Vol. 3, Issue 1: 1-7. https://doi.org/10.25236/IJFET.2021.030101.
[1] Gao Song. Application of Deep Learning in Airport Visibility Prediction. Computer Products and Circulation, 2020(04):260.（in Chinese）
[2] Wang Nan, Zhu Lei, Zhou Jianjun, Liu Qian, Yang Hongru. Interpretation and application of EC fine grid products in the low visibility prediction of Urumqi Airport. Desert and Oasis Meteorology, 2020, 14(02): 81-89 .（in Chinese）
[3] Zhu Guoliang. Airport visibility prediction model based on MLP neural network. Science and Technology Innovation and Application, 2018(18):1-4.（in Chinese）
[4] Natalia Fedorova, Vladimir Levit, Aliton Oliveira da Silva, Deydila Michele Bonfim dos Santos. Low Visibility Formation and Forecasting on the Northern Coast of Brazil. Pure and Applied Geophysics,2013,170(4).
[5] Lei Zhu,Guodong Zhu,Lei Han,Nan Wang. The Application of Deep Learning in Airport Visibility Forecast. Atmospheric and Climate Sciences,2017,7(3).
[6] Hongru Yang, Nan Wang, Yulin Qin, Dawei Fan. Interpretation of EC Fine Grid Numerical Prediction Products in the Forecast of Frozen Fog in Urumqi Airport. Journal of Geoscience and Environment Protection,2018,6(9).
[7] Wang Nan, Zhu Lei, Zhou Jianjun, Liu Qian, Yang Hongru. Interpretation and application of EC fine grid products in the low visibility prediction of Urumqi Airport. Desert and Oasis Meteorology, 2020, 14(02): 81-89 .（in Chinese）
[8] S. Goswami,S. Chaudhuri,D. Das,I. Sarkar,D. Basu. Adaptive neuro-fuzzy inference system to estimate the predictability of visibility during fog over Delhi, India. Meteorological Applications,2020, 27(2).
[9] Feng Hanzhong, Chen Yongyi, Cheng Yongqin, Luo Kesheng. Research on low-visibility weather forecasting methods at Shuangliu Airport. Journal of Applied Meteorology, 2006(01): 94-99.（in Chinese）
[10] J. Güldner. A model-based approach to adjust microwave observations for operational applications: results of a campaign at Munich Airport in winter 2011/2012. Atmospheric Measurement Techniques,2013,6(10).