A Knowledge-Data-Driven Emergency Decision Support Method for Aviation Support Operation Risk

Yihui Gong; Jing Liu; Hongwei Guo; Tian Bai; Chengyu Li; Zhaoting Yuan

doi:10.2991/978-94-6463-256-9_31

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A Knowledge-Data-Driven Emergency Decision Support Method for Aviation Support Operation Risk

Authors

Yihui Gong¹, Jing Liu², Hongwei Guo¹^{, *}, Tian Bai², Chengyu Li¹, Zhaoting Yuan¹

¹School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 100081, China

²China State Shipbuilding Corporation System Engineering Research Institute, Beijing, China

^*Corresponding author. Email: guohongwei@bit.edu.cn

Corresponding Author

Hongwei Guo

Available Online 9 October 2023.

DOI: 10.2991/978-94-6463-256-9_31 How to use a DOI?
Keywords: Case-based Reasoning; Rule-based Reasoning; Aviation Support System; Risk Analysis; Emergency Decision
Abstract: The aviation support system is the core of ensuring the safe takeoff and landing of aircraft and orderly operation. However, when the aviation support task is carried out, there are many factors leading to disasters, with a wide range of impacts, leading to difficult safety management. Therefore, it is necessary to avoid the occurrence of risks and quickly curb the spread of risks. In view of the problems of high timeliness and complexity of aviation support operation risk decision-making, the characteristic attributes of three parts of the disposal process are given through the analysis of the decision-making process. A knowledge-data-driven emergency decision support method for aviation support operation risk, based on case-based reasoning and rule-based reasoning is proposed, which can quickly generate effective decision schemes. With the verification of 20 cases of aviation support operation risk, the performance of the hybrid method was better than pure CBR or RBR.
Copyright: © 2024 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)
Series: Advances in Economics, Business and Management Research
Publication Date: 9 October 2023
ISBN: 10.2991/978-94-6463-256-9_31
ISSN: 2352-5428
DOI: 10.2991/978-94-6463-256-9_31 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Yihui Gong
AU  - Jing Liu
AU  - Hongwei Guo
AU  - Tian Bai
AU  - Chengyu Li
AU  - Zhaoting Yuan
PY  - 2023
DA  - 2023/10/09
TI  - A Knowledge-Data-Driven Emergency Decision Support Method for Aviation Support Operation Risk
BT  - Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)
PB  - Atlantis Press
SP  - 293
EP  - 301
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-256-9_31
DO  - 10.2991/978-94-6463-256-9_31
ID  - Gong2023
ER  -

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