Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods
Based on the hourly visibility data, visibility and its changes during 2010–2020 at monthly and annual time scales over 47 international airports in China are investigated, and nine artificial-intelligence-based hourly visibility prediction models are trained (hourly data in 2018–2019) and tested (h...
| প্রধান লেখক: | , , , , , , , , |
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| বিন্যাস: | প্রবন্ধ |
| ভাষা: | English |
| প্রকাশিত: |
MDPI AG
2022-01-01
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| মালা: | Atmosphere |
| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | https://www.mdpi.com/2073-4433/13/1/75 |
| _version_ | 1827666758431932416 |
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| author | Jin Ding Guoping Zhang Shudong Wang Bing Xue Jing Yang Jinbing Gao Kuoyin Wang Ruijiao Jiang Xiaoxiang Zhu |
| author_facet | Jin Ding Guoping Zhang Shudong Wang Bing Xue Jing Yang Jinbing Gao Kuoyin Wang Ruijiao Jiang Xiaoxiang Zhu |
| author_sort | Jin Ding |
| collection | DOAJ |
| description | Based on the hourly visibility data, visibility and its changes during 2010–2020 at monthly and annual time scales over 47 international airports in China are investigated, and nine artificial-intelligence-based hourly visibility prediction models are trained (hourly data in 2018–2019) and tested (hourly data in 2020) at these airports. The analyses show that the visibility of airports in eastern and central China is at a poor level all year round, and LXA (in Lhasa) has good visibility all year round. Airports in south and the northwest China have better visibility from May to October and poorer visibility from November to April. In all months, the increasing visibility mainly occurs in the central, northeast and coastal areas of China, while decreasing visibility mainly appears in the western and northern parts of China. In spring, summer and autumn, the changes difference between east and west is particularly obvious. This East–West distribution of trends is obviously different from the North–South distribution shown by the mean. For all airports, good visibility mainly occurs from 14:00–18:00 p.m. Beijing Time, while poor visibility mainly concentrates from 22:00 p.m. to 12:00 p.m. the next day, especially between 3:00–9:00 a.m. Our proposed artificial intelligence algorithm models can be reasonably used in airport visibility prediction. In particular, most algorithm models have the best results in the visibility prediction over HFE (in Hefei) and SJW (in Shijiazhuang). On the contrary, the worst forecast results appear at LXA and LHW (in Lanzhou) airports. The prediction results of airport visibility in the cold season (October–December) are better than those in the warm season (May–September). Among the algorithm models, the prediction performance of the RF-based model is the best. |
| first_indexed | 2024-03-10T01:56:13Z |
| format | Article |
| id | doaj.art-aa3083e1ee5146e39d1ce48e87464de3 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-10T01:56:13Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-aa3083e1ee5146e39d1ce48e87464de32023-11-23T12:56:45ZengMDPI AGAtmosphere2073-44332022-01-011317510.3390/atmos13010075Forecast of Hourly Airport Visibility Based on Artificial Intelligence MethodsJin Ding0Guoping Zhang1Shudong Wang2Bing Xue3Jing Yang4Jinbing Gao5Kuoyin Wang6Ruijiao Jiang7Xiaoxiang Zhu8Public Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaPublic Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaPublic Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaPublic Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaPublic Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaPublic Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaPublic Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaPublic Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaPublic Meteorological Service Center, China Meteorological Administration, Beijing 100081, ChinaBased on the hourly visibility data, visibility and its changes during 2010–2020 at monthly and annual time scales over 47 international airports in China are investigated, and nine artificial-intelligence-based hourly visibility prediction models are trained (hourly data in 2018–2019) and tested (hourly data in 2020) at these airports. The analyses show that the visibility of airports in eastern and central China is at a poor level all year round, and LXA (in Lhasa) has good visibility all year round. Airports in south and the northwest China have better visibility from May to October and poorer visibility from November to April. In all months, the increasing visibility mainly occurs in the central, northeast and coastal areas of China, while decreasing visibility mainly appears in the western and northern parts of China. In spring, summer and autumn, the changes difference between east and west is particularly obvious. This East–West distribution of trends is obviously different from the North–South distribution shown by the mean. For all airports, good visibility mainly occurs from 14:00–18:00 p.m. Beijing Time, while poor visibility mainly concentrates from 22:00 p.m. to 12:00 p.m. the next day, especially between 3:00–9:00 a.m. Our proposed artificial intelligence algorithm models can be reasonably used in airport visibility prediction. In particular, most algorithm models have the best results in the visibility prediction over HFE (in Hefei) and SJW (in Shijiazhuang). On the contrary, the worst forecast results appear at LXA and LHW (in Lanzhou) airports. The prediction results of airport visibility in the cold season (October–December) are better than those in the warm season (May–September). Among the algorithm models, the prediction performance of the RF-based model is the best.https://www.mdpi.com/2073-4433/13/1/75visibilityinternational airportspredictionartificial intelligence |
| spellingShingle | Jin Ding Guoping Zhang Shudong Wang Bing Xue Jing Yang Jinbing Gao Kuoyin Wang Ruijiao Jiang Xiaoxiang Zhu Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods Atmosphere visibility international airports prediction artificial intelligence |
| title | Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods |
| title_full | Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods |
| title_fullStr | Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods |
| title_full_unstemmed | Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods |
| title_short | Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods |
| title_sort | forecast of hourly airport visibility based on artificial intelligence methods |
| topic | visibility international airports prediction artificial intelligence |
| url | https://www.mdpi.com/2073-4433/13/1/75 |
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