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

Yihui Gong, Jing Liu, Hongwei Guo (), Tian Bai, Chengyu Li and Zhaoting Yuan
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Yihui Gong: Beijing Institute of Technology, School of Mechanical Engineering
Jing Liu: China State Shipbuilding Corporation System Engineering Research Institute
Hongwei Guo: Beijing Institute of Technology, School of Mechanical Engineering
Tian Bai: China State Shipbuilding Corporation System Engineering Research Institute
Chengyu Li: Beijing Institute of Technology, School of Mechanical Engineering
Zhaoting Yuan: Beijing Institute of Technology, School of Mechanical Engineering

A chapter in Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), 2024, pp 293-301 from Springer

Abstract: 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.

Keywords: Case-based Reasoning; Rule-based Reasoning; Aviation Support System; Risk Analysis; Emergency Decision (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-256-9_31

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