A Knowledge-Data-Driven Emergency Decision Support Method for Aviation Support Operation Risk
- DOI
- 10.2991/978-94-6463-256-9_31How 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.
Cite this article
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 -