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Topological data analysis for aviation applications

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  • Li, Max Z.
  • Ryerson, Megan S.
  • Balakrishnan, Hamsa

Abstract

Aviation data sets are increasingly high-dimensional and sparse. Consequently, the underlying features and interactions are not easily uncovered by traditional data analysis methods. Recent advancements in applied mathematics introduce topological methods, offering a new approach to obtain these features. This paper applies the fundamental notions underlying topological data analysis and persistent homology (TDA/PH) to aviation data analytics. We review past aviation research that leverage topological methods, and present a new computational case study exploring the topology of airport surface connectivity. In each case, we connect abstract topological features with real-world processes in aviation, and highlight potential operational and managerial insights.

Suggested Citation

  • Li, Max Z. & Ryerson, Megan S. & Balakrishnan, Hamsa, 2019. "Topological data analysis for aviation applications," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 149-174.
    • Handle: RePEc:eee:transe:v:128:y:2019:i:c:p:149-174
    DOI: 10.1016/j.tre.2019.05.017
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    References listed on IDEAS

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    1. Li, Max Z. & Ryerson, Megan S., 2019. "Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 111-130.
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    3. Rajendran, Suchithra & Srinivas, Sharan, 2020. "Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).

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