气候变化领域集成服务门户(CCPortal): Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record (QAR) Data Analysis

CCPortal

DOI	10.1007/s00376-024-3195-x
	Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record (QAR) Data Analysis
	Zhuang, Zibo; Lin, Kunyun; Zhang, Hongying; Chan, Pak-Wai
发表日期	2024
ISSN	0256-1530
EISSN	1861-9533
起始页码	41
结束页码	6
卷号	41 期号:6
英文摘要	As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry, it has become imperative to monitor and mitigate these threats to ensure civil aviation safety. The eddy dissipation rate (EDR) has been established as the standard metric for quantifying turbulence in civil aviation. This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder (QAR) data. The detection of atmospheric turbulence is approached as an anomaly detection problem. Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events. Moreover, comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available. In summary, the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data, comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms. This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.
英文关键词	turbulence detection; symbolic classifier; quick access recorder data
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:001194951800001
来源期刊	ADVANCES IN ATMOSPHERIC SCIENCES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/293616
作者单位	Civil Aviation University of China; Civil Aviation University of China
推荐引用方式 GB/T 7714	Zhuang, Zibo,Lin, Kunyun,Zhang, Hongying,et al. Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record (QAR) Data Analysis[J],2024,41(6).
APA	Zhuang, Zibo,Lin, Kunyun,Zhang, Hongying,&Chan, Pak-Wai.(2024).Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record (QAR) Data Analysis.ADVANCES IN ATMOSPHERIC SCIENCES,41(6).
MLA	Zhuang, Zibo,et al."Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record (QAR) Data Analysis".ADVANCES IN ATMOSPHERIC SCIENCES 41.6(2024).