机场时间配置结构由航班延误预测驱动
1College of Air Traffic Management, Civil Aviation University of China, Tianjin, 300300, China.
Scientific reports
|August 12, 2024
概括
这项研究通过使用历史数据和机器学习来预测航班时间表和延误,优化了机场时机管理. 开发的模型确保了及时运营,预测间隔内的航班延迟不到15分钟.
科学领域:
- 航空运营研究 航空运营研究
- 数据科学在运输中的应用
- 机场老虎机管理 机场老虎机管理
背景情况:
- 机场时机管理平衡了市场需求和运营能力.
- 为繁忙的机场开发高效的18-24小时时间表是一个重大挑战.
- 现有的机槽参数必须与运营效率和市场需求波动保持一致.
研究的目的:
- 开发一个机场时间结构和航班延误水平的预测模型.
- 将天气条件和运营限制纳入时机管理.
- 提高民用航空时段安排的可靠性和效率.
主要方法:
- 利用历史飞行和天气数据进行分析.
- 应用K-means集群和部分最小平方回归用于时间结构建模.
- 采用集体学习,特别是随机森林,用于航班延误预测.
主要成果:
- 随机森林在回归和预测任务中表现出高准确度.
- 成功地集成了时间配置限制 (基于天气) 与延迟预测.
- 在定义的时间参数间隔内的飞行平均延误小于15分钟.
结论:
- 拟议的模型有效地预测了航班延误,并优化了航班时间表.
- 在预测的间隔内实现不到15分钟的平均延误会提高运营期望.
- 这种方法提供了一个强大的解决方案,用于在不同条件下管理机场繁忙的机时间表.
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