Research on Domain Entity Extraction in Civil Aviation Safety

Jiao, Yang; Han, Jingru; Xu, Bohao; Xiao, Ming; Shen, Binnan; Sun, Hong-Jin

doi:10.1109/iccasit53235.2021.9633439

Cited by 3 publications

(1 citation statement)

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“…Since the definition of convolutional layer is known, the whole neural network can be set up. In general, the subject graph convolutional neural network is composed of three convolutional layer [4], and the mathematical expression of the whole graph convolutional neural network is as follows:…”

Section: Model Establishment and Solutionmentioning

confidence: 99%

Aviation Safety QAR Data Mining and Statistical Analysis

Zhan¹,

Zhang²,

Luo³

et al. 2023

ACC

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Flight safety is the fundamental guarantee for the survival and development of civil aviation transport industry. Serious flight accidents will not only bring huge economic losses to airlines, but also pose a great threat to the life safety of passengers. Therefore, we need to pay close attention to flight safety. Firstly, the pre-analysis is carried out, and it is found that the quantity directly related to the aircraft manoeuvring is the disc quantity and the rod quantity, which correspond to roll manoeuvring and pitch manoeuvring respectively. After that, cluster analysis and graph neural network model introduced attention mechanism were used to train the data, and it was concluded that the most important operational factors affecting the flight of aircraft were rod size and attitude. According to the model, the reason for the heavy landing is traced back: "It is because of the incorrect loose rod that the rod size and attitude are abnormal, which makes the G-value curve of the landing significantly convex". Finally, the advantages and disadvantages of the model are evaluated and the sensitivity is analyzed. The model established in this paper can be extended to evaluate the stability of social and economic operation.

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Section: Model Establishment and Solutionmentioning

confidence: 99%