Applying Machine Learning to Enhance Runway Safety Through Runway Excursion Risk Mitigation-Reference-Cited by-同舟云学术

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Applying Machine Learning to Enhance Runway Safety Through Runway Excursion Risk Mitigation

Published:2022-02 Issue:2 Volume:19 Page:98-112
ISSN:2327-3097
Container-title:Journal of Aerospace Information Systems
language:en
Short-container-title:Journal of Aerospace Information Systems

Author:

Odisho Edwin V.¹,Truong Dothang¹^ORCID,Joslin Robert E.¹

Affiliation:

1. Embry–Riddle Aeronautical University, Daytona Beach, Florida 32114

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Aerospace Engineering

Link

https://arc.aiaa.org/doi/pdf/10.2514/1.I010972

Reference26 articles.

1. Data mining application on aviation accident data for predicting topmost causes for accidents

2. Analysis of Flight Data Using Clustering Techniques for Detecting Abnormal Operations

3. Anomaly Detection in General-Aviation Operations Using Energy Metrics and Flight-Data Records

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1. A Comparative Study of Machine Learning Techniques for Aircraft Loss of Control Prediction*;2024 American Control Conference (ACC);2024-07-10

2. Wind Limitations at Madeira International Airport: A Deep Learning Prediction Approach;IEEE Access;2024

3. IMTCN: An Interpretable Flight Safety Analysis and Prediction Model Based on Multi-Scale Temporal Convolutional Networks;IEEE Transactions on Intelligent Transportation Systems;2024-01

4. Predicting the Severity of Runway Excursions from Aviation Safety Reports;Journal of Aerospace Information Systems;2023-09

5. The effect of COVID-19 on self-reported safety incidents in aviation: An examination of the heterogeneous effects using causal machine learning;Journal of Safety Research;2023-02

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