Prediction of Flight Taxi-out Time in A Busy Airport Based on LWSVR

Authors

Zhiwei Xing, 1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China; ;
Songyue Jiang, 1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China; ;
Luo Qian, 2. The Second Research Institute of Civil Aviation Administration of China, Chengdu 610041, China;
Luo Xiao, 2. The Second Research Institute of Civil Aviation Administration of China, Chengdu 610041, China;

Abstract

Abstract: Aiming at improving the accuracy of predicting the flight taxi-out time in a busy airport, based on the local regression and weighted support vector regression, a prediction model of the locally weighted support vector regression is proposed. The model uses the K nearest neighbor method to reduce the capacity of the training sample set and build a predictive model for each predicted sample. The bandwidth parameter of the Gaussian weighting function is optimized with the Mahalanobis distance between the forecast sample and training samples, and the weighting coefficients are obtained. Combining the airport departure flight data in simulation analysis, the experimental results show that the accuracy of LWSVR within the error range is 83.33%, and the model is more stable.

Recommended Citation

Xing, Zhiwei; Jiang, Songyue; Qian, Luo; and Xiao, Luo (2020) "Prediction of Flight Taxi-out Time in A Busy Airport Based on LWSVR," Journal of System Simulation: Vol. 32: Iss. 5, Article 20.
DOI: 10.16182/j.issn1004731x.joss.18-0598
Available at: https://dc-china-simulation.researchcommons.org/journal/vol32/iss5/20

First Page

927

Revised Date

2018-12-17

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.18-0598

Last Page

935

CLC

U8;TP391.9

Recommended Citation

Xing Zhiwei, Jiang Songyue, Luo Qian, Luo Xiao. Prediction of Flight Taxi-out Time in A Busy Airport Based on LWSVR[J]. Journal of System Simulation, 2020, 32(5): 927-935.

DOI

10.16182/j.issn1004731x.joss.18-0598