基于遗传算法组合预测模型的空域流量预测系统构建

The Research of Airspace Traffic Flow Prediction System

航班总量的持续增长使得航班安全保障的压力不断加大。在空域资源有限、航空管制工作繁重的大型国际机场,航班动态信息的准确、可靠性将为制定有效地管制调配措施提供有力的依据。为了准确预测特定区域中某个航路点在某一时间段的航班流量,给管制人员提供参考,便于提前灵活、合理地制定管制策略,避免空域资源浪费,为各级决策部门制定发展战略与规划提供重要依据。基于不同航班流量信息源建立组合预测模型,通过遗传算法对组合模型的权重值进行优化,并根据西安管制区域构建出了空域流量预测系统的设计构架。

The continued growth of the total flights makes the safety and security of flights increasing pressure, Limited resources in the airspace, air traffic control workload of international airport, the accuracy and reliability of the flight dynamic information provide the basis for the measures of air traffic control effectively. In this paper, the solution to these problems is to focus on predict the flight flow in the specific control area and flight route point at a specific time interval, providing reference flow information to air traffic controllers so that they can lay down control program flexibly in advance and avoid wasting airspace resource, offering a important evidence for air traffic control decision-making authority to establish future developmental strategy and program. This paper established combination forecasting model based on different flight flow information source, optimized the weights of the combined model based on genetic algorithm and built a structure of Airspace Traffic Flow Prediction System according to the Xi＇an air traffic control area.