Airport flight ground service time prediction with missing data using graph convolutional neural network imputation and bidirectional sliding mechanism-Reference-Cited by-同舟云学术

Airport flight ground service time prediction with missing data using graph convolutional neural network imputation and bidirectional sliding mechanism

Published:2023-01 Issue: Volume:133 Page:109941
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Liu Chang^ORCID,Chen YanRu,Wang Hao,Zhang YuanYuan,Dai Xuewu,Luo Qian,Chen LiangYin^ORCID

Publisher

Elsevier BV

Subject

Software

Reference46 articles.

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2. Sliding window change point detection based dynamic network model inference framework for airport ground service process;Liu;Knowl.-Based Syst.,2022

3. Integration of turnaround and aircraft recovery to mitigate delay propagation in airline networks;Evler;Comput. Oper. Res.,2022

4. A new airport collaborative decision making algorithm based on deferred acceptance in a two-sided market;de Arruda Junior;Expert Syst. Appl.,2015

5. A prediction method based on neural network for flight turnaround time at airport;Gao,2015

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