基于灰色/回归+马尔可夫模型的航班流量预测
Flight Traffic Prediction Based on Gray/Regression+Markov Models
赵江鸽 1周洁敏1
作者信息
- 1. 南京航空航天大学民航学院,江苏南京 211100
- 折叠
摘要
合理准确的航班流量预测是制定相关管制方案和地面保障程序的前提.建立灰色/回归+马尔可夫组合模型进行航班流量预测,并以机场实际航班流量数据为例进行模型验证.首先使用灰色模型和多项式回归对航班流量的训练样本进行趋势性预测,选取精度高的模型作为趋势模型.其次用马尔可夫模型对预测结果进行修正并比较修正前后平均相对误差,结果表明,修正后的误差从1.07％降低到0.64％.最后对测试样本进行验证,其相对误差在5％以内,验证了模型的可行性.此研究可为机场及时调整管制方案、提高运行效率、保障运行安全提供理论依据.
Abstract
Reasonable and accurate flight flow forecast is the prerequisite for formulating relevant control plans and ground support procedures.A gray/regression+Markov combination model is estab-lished to predict flight flow,and actual flight flow data at the airport are used as an example to verify the model.Firstly,the gray model and polynomial regression are used to predict the trend of the training samples of flight traffic,and the model with high accuracy is selected as the trend model.Secondly,the Markov model is used to correct the prediction results and the average relative error before and after the correction is compared.The results show that the error after correction is reduced from 1.07％to 0.64％.Finally,the test sample is verified and the relative error is within 5％,which verifies the feasibili-ty of the model.This research can provide a theoretical basis for timely adjustment of control plans,im-provement of operational efficiency,and ensuring operational safety.
关键词
航班流量预测/灰色预测/多项式回归/马尔可夫链Key words
flight traffic forecasting/gray forecasting/polynomial regression/Markov chains引用本文复制引用
出版年
2024
NETL
NSTL
万方数据