Causal Discovery of Flight Service Process Based on Event Sequence
نویسندگان
چکیده
The development of the civil aviation industry has continuously increased requirements for efficiency airport ground support services. In existing research, there not yet been a process model that directly obtains from log to study causal relationship between service nodes and flight delays. Most studies mainly use machine learning methods predict delays, they are based on is an ideal model. did conduct in-depth mechanism behind link reveal true cause Therefore, certain deviation in prediction delays by learning, research actual process. it practical significance obtain guarantee analyze its causality. However, factor discovery only do when assumption sufficiency established does consider existence latent variables. this article proposes framework realize factors without assuming sufficiency. optimized fuzzy mining used as benchmark model, local algorithm discover factors. Under framework, paper new Markov blanket assume uses data sets testing. Finally, among nodes. proposed competitive advantage accuracy, F1, other aspects algorithm. It avoids occurrence dimensional disaster. Through analysis safety reason node discovered method, found unreasonable scheduling personnel important frequent at airport.
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ژورنال
عنوان ژورنال: Journal of Advanced Transportation
سال: 2021
ISSN: ['0197-6729', '2042-3195']
DOI: https://doi.org/10.1155/2021/2869521