Situation Assessment of Air Traffic Based on Complex Network Theory and Ensemble Learning
With the rapid development of the air transportation industry, the air traffic situation is becoming more and more complicated. Determining the situation of air traffic is of great significance to ensure the safety and smoothness of air traffic. The strong subjectivity of assessment criteria, inaccu...
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| Format: | Article |
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MDPI AG
2023-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/21/11957 |
| _version_ | 1797632130121990144 |
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| author | Fei Liu Jiawei Li Xiangxi Wen Yu Wang Rongjia Tong Shubin Liu Daxiong Chen |
| author_facet | Fei Liu Jiawei Li Xiangxi Wen Yu Wang Rongjia Tong Shubin Liu Daxiong Chen |
| author_sort | Fei Liu |
| collection | DOAJ |
| description | With the rapid development of the air transportation industry, the air traffic situation is becoming more and more complicated. Determining the situation of air traffic is of great significance to ensure the safety and smoothness of air traffic. The strong subjectivity of assessment criteria, inaccurate assessment results and weak systemic assessment method are the main problems in air traffic situation assessment research. The aim of our research is to present an objective and accurate situation assessment method for air traffic systems. The paper presents a model to assess air traffic situation based on the complex network theory and ensemble learning. The air traffic weighted network model was introduced to systematically describe the real state of an air traffic system. Assessment criteria based on the complex network analysis method can systematically reflect the operational state of an air traffic weighted network system. We transformed the air traffic situation assessment into a binary classification, which makes situation assessment objective and accurate. Ensemble learning was introduced to improve the classification accuracy, which further improves the accuracy of the situation assessment model. The model was trained and tested on the dataset of the East China air traffic weighted network in 2019. Its average classification accuracy is 0.98. The recall and precision rates both exceed 0.95. Experiments have confirmed that the situation assessment model can accurately output air traffic situation value and situation level. Furthermore, the assessment results are consistent with the real operational situation of the air traffic in East China. |
| first_indexed | 2024-03-11T11:33:31Z |
| format | Article |
| id | doaj.art-4d66b256282546aeae097814c16571a7 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T11:33:31Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4d66b256282546aeae097814c16571a72023-11-10T14:59:18ZengMDPI AGApplied Sciences2076-34172023-11-0113211195710.3390/app132111957Situation Assessment of Air Traffic Based on Complex Network Theory and Ensemble LearningFei Liu0Jiawei Li1Xiangxi Wen2Yu Wang3Rongjia Tong4Shubin Liu5Daxiong Chen6Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, ChinaPLA Troops No. 93735, Tianjin 310700, ChinaAir Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, ChinaPLA Troops No. 66137, Beijing 100032, ChinaPLA Troops No. 94188, Xi’an 710050, ChinaPLA Troops No. 93735, Tianjin 310700, ChinaPLA Troops No. 94755, Zhangzhou 363000, ChinaWith the rapid development of the air transportation industry, the air traffic situation is becoming more and more complicated. Determining the situation of air traffic is of great significance to ensure the safety and smoothness of air traffic. The strong subjectivity of assessment criteria, inaccurate assessment results and weak systemic assessment method are the main problems in air traffic situation assessment research. The aim of our research is to present an objective and accurate situation assessment method for air traffic systems. The paper presents a model to assess air traffic situation based on the complex network theory and ensemble learning. The air traffic weighted network model was introduced to systematically describe the real state of an air traffic system. Assessment criteria based on the complex network analysis method can systematically reflect the operational state of an air traffic weighted network system. We transformed the air traffic situation assessment into a binary classification, which makes situation assessment objective and accurate. Ensemble learning was introduced to improve the classification accuracy, which further improves the accuracy of the situation assessment model. The model was trained and tested on the dataset of the East China air traffic weighted network in 2019. Its average classification accuracy is 0.98. The recall and precision rates both exceed 0.95. Experiments have confirmed that the situation assessment model can accurately output air traffic situation value and situation level. Furthermore, the assessment results are consistent with the real operational situation of the air traffic in East China.https://www.mdpi.com/2076-3417/13/21/11957air traffic networksituation assessmentcomplex networkensemble learning |
| spellingShingle | Fei Liu Jiawei Li Xiangxi Wen Yu Wang Rongjia Tong Shubin Liu Daxiong Chen Situation Assessment of Air Traffic Based on Complex Network Theory and Ensemble Learning Applied Sciences air traffic network situation assessment complex network ensemble learning |
| title | Situation Assessment of Air Traffic Based on Complex Network Theory and Ensemble Learning |
| title_full | Situation Assessment of Air Traffic Based on Complex Network Theory and Ensemble Learning |
| title_fullStr | Situation Assessment of Air Traffic Based on Complex Network Theory and Ensemble Learning |
| title_full_unstemmed | Situation Assessment of Air Traffic Based on Complex Network Theory and Ensemble Learning |
| title_short | Situation Assessment of Air Traffic Based on Complex Network Theory and Ensemble Learning |
| title_sort | situation assessment of air traffic based on complex network theory and ensemble learning |
| topic | air traffic network situation assessment complex network ensemble learning |
| url | https://www.mdpi.com/2076-3417/13/21/11957 |
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