Flight delay prediction model based on CART algorithm

Abstract

Abstract: Aiming at the flight delay problem of civil aviation airliners, this paper constructs a flight delay prediction model based on random forest model and classification regression decision tree(CART) algorithm, on which a large amount of training are conducted by using the real data set from large China airports. With the training results of Logistic regression algorithm, K-nearest neighbor(KNN) regression algorithm and decision tree algorithm, and with the fitting results, it is concluded that this method can deal with high latitude data with good generalization ability, and reduce the possibility of over fitting. The fitting degree R2 of the model can reach 0.83.

Key words: , flight delay, random forest model, classification and regression tree(CART) algorithm

CLC Number:

V355.1

WANG Hui , ZHANG Wenjie , LIU jie , CHEN Linfeng , LI Zenan. Flight delay prediction model based on CART algorithm[J]. Journal of Civil Aviation University of China, 2022, 40(3): 35-40.

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