查询结果:   徐涛,丁杨,卢敏.基于级联BP神经网络的航班撤轮挡时刻预测[J].计算机应用与软件,2019,36(6):226 - 232.
中文标题
基于级联BP神经网络的航班撤轮挡时刻预测
发表栏目
算法
摘要点击数
825
英文标题
FLIGHT OFF-BLOCK TIME PREDICTION BASED ON CASCADED BP NEURAL NETWORK
作 者
徐涛 丁杨 卢敏 Xu Tao Ding Yang Lu Min
作者单位
中国民航大学计算机科学与技术学院 天津 300300 中国民航信息技术科研基地 天津 300300 民航旅客服务智能化应用技术重点实验室 北京 101318   
英文单位
College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China Information Technology Research Base of Civil Aviation Administration of China, Tianjin 300300, China Key Laboratory of Intelligent Passenger Service of Civil Aviation, CAAC, Beijing 101318, China   
关键词
航班撤轮挡时刻预测 BP神经网络 级联模型 里程碑事件 过拟合
Keywords
Flight off-block time prediction BP neural network Cascaded model Milestone event Overfitting
基金项目
国家自然科学基金项目(61502499);民航旅客服务智能化应用技术重点实验室项目;中央高校基本科研业务费科研专项(3122015Z007)
作者资料
徐涛,教授,主研领域:数据挖掘,智能信息处理。丁杨,硕士生。卢敏,讲师。 。
文章摘要
合理的航班协同离场前排序可以提高机场、航空公司、空管等部门的运行效率和可预测性,减少航班起飞前的等待时间。准确地预测航班撤轮挡时刻是建立航班起飞顺序的先决条件,对调整起飞前航班排序和计算航班起飞时间具有重要的决策意义。提出一个基于级联BP神经网络的航班撤轮挡时刻预测模型。该模型分别在航班过站过程的不同时刻进行航班撤轮挡时刻的预测,并进行过拟合研究。实验结果表明,与目前采用的经验统计预测模型相比,在相同时刻,该预测模型具有更高的预测准确率。
Abstract
A reasonable arrangement of pre-departure sequence of flights can improve the efficiency and predictability of airport, airline and blank pipe, and reduce the waiting time before the aircrafts take off. Accurate prediction of the flight off-block time is a prerequisite for the establishment of a pre-departure sequence, which has important decision significance for adjusting the flight departure order and calculating the flight departure time. This paper proposed a flight off-block time prediction model based on cascaded BP neural network. The model predicted the flight off-block time at different times of the flight turnaround process, and made over-fitting study.The experimental results show that compared with the empirical statistical prediction model currently used, the model has higher prediction accuracy at the same time.
下载PDF全文