Classification algorithms and applications for flight delay prediction based on unbalanced data

Jingyi Qu; Bo Chen

doi:10.1117/12.2681061

23 May 2023 Classification algorithms and applications for flight delay prediction based on unbalanced data

Jingyi Qu, Bo Chen

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126451O (2023) https://doi.org/10.1117/12.2681061
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

By predicting flight delays, economic losses caused by delay situations can be effectively prevented and reduced. A classification algorithm for flight delay prediction based on unbalanced data is proposed to solve the problem of unbalanced number of delayed and non-delayed samples in the process of flight delay prediction. Firstly, a multi-classification model based on the CycleMLP algorithm is proposed for flight delay prediction. Secondly, the CycleMLP algorithm is improved by using the Focal Loss modified cross-entropy loss function to build the final classification model for flight delay prediction. And the experimental results show that the improved model has better prediction results for delayed flights, with a 5.54% increase in average macro precision and 1.86% increase in accuracy. Finally, the flight delay prediction results are published in the mobile APP application system to provide corresponding advice to passengers and airport departments.

Citation Download Citation

Jingyi Qu and Bo Chen "Classification algorithms and applications for flight delay prediction based on unbalanced data", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126451O (23 May 2023); https://doi.org/10.1117/12.2681061

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