管理信息系统的特征及发展趋势

文章从“四字格”在报刊译文中的主要作用及其运用场合两个方面进行了较为详细的探讨，并对如何恰当地运用“四字格”词组作了简要的阐明。     

Strategic flight assignment approach based on multi-objective parallel evolution algorithm with dynamic migration interval

The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by reasonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimization problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm(MPEA) framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is proposed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution(CC) algorithm combined with non-dominated sorting genetic algorithm II(NSGA-II) is introduced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multiobjective genetic algorithm(MOGA), multi-objective evolutionary algorithm based on decomposition(MOEA/D), CC-based multi-objective algorithm(CCMA) as well as other two MPEAs with different migration interval strategies.     

终端区进场交通流广义跟驰行为与复杂相变分析

空中交通流特性分析是空中交通流理论研究的重要内容,是空中交通管理的重要依据。基于终端区交通流混杂动力特征,采用模糊逻辑方法提出了航空器动态期望间隔控制策略,运用"刺激-反射"跟驰理论和局域先到先服务(FCFS)的原则建立了终端区交通流广义跟驰模型,并基于NetLogo构建了终端区交通流多智能体仿真平台,结合广州白云机场(ZGGG)02R跑道进场实例,演析了终端区进场交通系统涌现行为,揭示了交通流的速度、密度和流量3个基本参数之间的相互关系,发掘了空中交通蕴含的自由态、畅行态、亚稳态、伪拥塞态和同步态等5个演变相态,剖析了不同交通组织、间隔标准和流控策略下交通流的相变规律。研究成果可为丰富完善空中交通流理论奠定部分基础,为科学管控空中交通提供重要基础支撑。     

Measuring air traffic complexity based on small samples

Air traffic complexity is an objective metric for evaluating the operational condition of the airspace.It has several applications,such as airspace design and traffic flow management.Therefore,identifying a reliable method to accurately measure traffic complexity is important.Considering that many factors correlate with traffic complexity in complicated nonlinear ways,researchers have proposed several complexity evaluation methods based on machine learning models which were trained with large samples.However,the high cost of sample collection usually results in limited training set.In this paper,an ensemble learning model is proposed for measuring air traffic complexity within a sector based on small samples.To exploit the classification information within each factor,multiple diverse factor subsets (FSSs) are generated under guidance from factor noise and independence analysis.Then,a base complexity evaluator is built corresponding to each FSS.The final complexity evaluation result is obtained by integrating all results from the base evaluators.Experimental studies using real-world air traffic operation data demonstrate the advantages of our model for small-sample-based traffic complexity evaluation over other stateof-the-art methods.     

空中交通监视电子地图平台设计

采用Java技术,从底层设计并实现了一个航空矢量电子地图平台,介绍了平台结构和设计要点。针对矢量电子地图中普遍存在的响应迟滞问题,提出了基于图层自检的多级过滤绘制方法,显著提高了地图响应速度。在处理监视数据时,采用基于混合门限的自适应刷新策略,有效地控制了平台资源负载情况,平台稳定性得以提高。     

Navigation Accuracy Category-Position Models and Estimate Position Uncertainty Calculations for TIS-B System

Navigation accuracy category-position (NACp) is an important parameter for system accuracy of traffic information service-broadcast (TIS-B), which is determined by estimate position uncertainty (EPU). Centered about the problems that the existing EPU calculation based on noise measurement is low in accuracy and unfit for describing uncorrected biases in target reports, this article analyses the traditional NACp model, and uses the least square estimation (LSE) in EPU calculation. Furthermore, it proposes an extended NACp model, which considers both noise and biases and acquires EPU estimation with the help of approximate multiplex Taylor expression. Analysis and simulation show that the proposed method not only leads to significant improvement of the accuracy of EPU calculation, but is fit for EPU calculation with tracking biases in TIS-B system as well. As such it can find application in practice to depict different kinds of error models in TIS-B system.     

基于空中交通密度的进场航班动态协同排序方法

为适应协同决策（CDM）需要，考虑空管、航空公司和机场的诉求，对进场航班动态协同排序问题进行了系统的研究。设计了一种进场航班动态排序方法，提出了一种时隙交换方法，建立了基于空中交通密度的进场航班协同排序模型，设计了精英保留的遗传算法和带精英策略的快速非支配排序遗传算法以求解所建模型，寻求进场航班动态协同排序的最优解。仿真结果表明，较基于滚动时域控制（RHC）方法，动态协同方法所得结果与排序开始时间无关，所需排序次数平均减少26.4%，且排序效率更高。较先到先服务（FCFS）方法，动态协同方法在高密度条件下各排序阶段最后一个进场航班的落地时间平均提前199.8 s；中密度条件下各排序阶段航班延误总时间平均减少29.9%，航班延误均衡性平均提高34.4%；低密度条件在航班正常率及航班延误公平性得到保证的前提下，满足时隙交换规则的排序阶段均增加了1种进场航班排序模式。所提方法可对进场航班进行优化排序，显著提高跑道容量，有效提升航班延误均衡性和航班延误公平性，契合协同决策理念，可实现三方协同排序。     

基于时间序列的空中交通流量灰预测模型算法

利用灰色预测理论,给出了一种空域内空中交通流量进行预测分析的算法——空中交通流量灰预测法,并利用Matlab软件作为计算工具,对管制区域、机场等空域流量的预测进行了仿真,计算结果以图表和图形的形式给出直观说明,验证了该算法的有效性。     

空中交通管制员的眼动行为与疲劳关系

在空中交通管制工作中,管制疲劳程度度量是一项需要长期研究的重要课题。实时测量管制员的疲劳程度,对航空运输系统的安全运行有重要意义。提出以眼动行为特征指标作为反映管制员疲劳程度的依据,利用faceLAB 5.0系统记录了管制员在正常状态和疲劳状态下进行管制模拟实验的眼动数据和绩效数据,分析了管制员的绩效数据与眨眼频率和瞳孔直径两种眼动指标在不同状态下的变化规律。研究发现与正常状态相比,管制员在疲劳状态下的眨眼频率增加,瞳孔直径减小。随着任务时间的增加,被试的绩效变差,眨眼频率增加,瞳孔直径减小,表明被试的工作状态从正常状态转为疲劳状态。统计分析结果说明,眨眼频率和瞳孔直径能够有效地检测管制员的疲劳状态,充分刻画不同工作时段管制员工作状态的变化,为开发实用的疲劳监测系统提供理论基础。     

求团之间最优路径的扩展双向广度搜索算法的改进

对求团之间最优路径的扩展扩度深度混合搜索算法进行了改进，将原算法中扩展双向广度搜索的三个过程合并为一个过程．改进算法当路径深度较小时与原算法等效，当路径深度较大时有更高的运行效率．