@inproceedings{07ee5bed6b8f49938b131d07ed31cd11,
title = "Research on Optimization Technology for Sequential Diagnostic Strategy based on Improved Quasi-Depth First Search Algorithm",
abstract = "Aiming at the problem that sequential diagnosis strategy optimization techniques for complex avionics systems are currently difficult to obtain optimal solutions quickly and effectively, this paper proposes an improved Quasi-Depth First Search (QDFS) algorithm based on the Rollout algorithm to optimize the design of sequential diagnosis strategies. The algorithm determines a test in two steps. Firstly, the Rollout algorithm is used to construct a temporary diagnostic tree with the selected test as the vertex, and then the {"}evaluation function{"}of the improved QDFS algorithm is used to calculate and compare the constructed temporary diagnostic tree to obtain the optimal diagnostic tree. The first test of the diagnostic tree is the current optimal test. Through a case study of sequential diagnosis strategy optimization, the results show that the improved algorithm can obtain a global optimal solution and generate an optimal diagnosis tree compared to the improved QDFS algorithm.",
keywords = "Avionics system, Diagnostic strategy, QDFS algorithm, Sequential fault diagnosis, Testability model",
author = "Xiaofeng Lv and Deyun Zhou and Fuqiang Li",
note = "Publisher Copyright: {\textcopyright} 2023 ACM.; 4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023 ; Conference date: 26-05-2023 Through 28-05-2023",
year = "2023",
month = may,
day = "26",
doi = "10.1145/3603781.3603902",
language = "英语",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "684--692",
booktitle = "Conference Proceeding - 2023 4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023",
}