Assessment of Wind Shear Severity in Airport Runway Vicinity using Interpretable TabNet approach and Doppler LiDAR Data-Reference-Cited by-同舟云学术

Assessment of Wind Shear Severity in Airport Runway Vicinity using Interpretable TabNet approach and Doppler LiDAR Data

Published:2024-01-10 Issue:1 Volume:38 Page:
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Khattak Afaq¹,Zhang Jianping²,Chan Pak-Wai³,Chen Feng¹

Affiliation:

1. The Key Laboratory of Infrastructure Durability and Operation Safety in Airfield of CAAC, College of Transportation Engineering, Tongji University, Jiading, Shanghai, China

2. The Second Research Institute of Civil Aviation Administration of China, Civil Unmanned Aircraft Traffic Management Key Laboratory of Sichuan Province, Chengdu, China

3. Hong Kong Observatory, Hong Kong, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2024.2302227

Reference53 articles.

1. Airport Council International. 2017. World airport traffic forecast 2017–2040 airport council international. Montréal, QC, USA: Airport Council International.

2. A Comparison of Resampling Techniques for Medical Data Using Machine Learning

3. Alkhamisi, A. O., and R. Mehmood. 2020, March. An ensemble machine and deep learning model for risk prediction in aviation systems. In 2020 6th Conference on Data Science and Machine Learning Applications (CDMA), 54–27. IEEE.

4. TabNet: Attentive Interpretable Tabular Learning

5. Batista, G. E., R. C. Prati, and M. C. Monard. 2005, September. Balancing strategies and class overlapping. International symposium on intelligent data analysis, 24–35. Berlin Heidelberg: Berlin, Heidelberg: Springer.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Scoping Review of Artificial Intelligence Applications in Airports;COMPUTATIONAL RESEARCH PROGRESS IN APPLIED SCIENCE &amp ENGINEERING;2024