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- Title
Visibility Prediction Based on Machine Learning Algorithms.
- Authors
Zhang, Yu; Wang, Yangjun; Zhu, Yinqian; Yang, Lizhi; Ge, Lin; Luo, Chun
- Abstract
In this study, ground observation data were selected from January 2016 to January 2020. First, six machine learning methods were used to predict visibility. We verified the accuracy of the method with and without principal components analysis (PCA) by combining actual examples with the European Centre for Medium-Range Weather Forecast (ECMWF) data and National Centers for Environmental Prediction (NECP) data. The results show that PCA can improve visibility prediction. Neural networks have high accuracy in machine learning algorithms. The initial visibility data plays an important role in the visibility forecast and can effectively improve forecast accuracy.
- Subjects
NATIONAL Centers for Environmental Prediction (U.S.); PRINCIPAL components analysis; MACHINE learning; ACCESS to information; SERVER farms (Computer network management)
- Publication
Atmosphere, 2022, Vol 13, Issue 7, p1125
- ISSN
2073-4433
- Publication type
Article
- DOI
10.3390/atmos13071125