基于管制员认知负荷和改进蚁群算法的扇区动态通行能力评估

针对现有动态通行能力的评估未考虑管制员认知负荷的不足,为了提高空中交通流量管理的准确性,构建了基于管制员认知负荷和改进蚁群算法的扇区动态通行能力评估模型。首先,构建了刻画扇区动态影响因素的动态飞行受限区模型,为了满足空中交通流量管理对速度的要求,改进了蚁群算法实现扇区动态管制引导路径规划;然后,提出了管制引导负荷强度的概念,扩展了管制员认知总负荷的概念,并将其应用于扇区动态通行能力评估模型的构建;最后,以三亚管制扇区为例,以15 min为间隔对未来2 h内9个时刻的扇区动态通行能力进行评估。实例验证结果表明所提评估模型计算得到的通行能力结果与实际运行结果相差1个架次,效果理想。     

图切割快速生成扇区的蚁群算法

扇区划分是平衡管制员工作负荷、提升空域通行能力的有效技术措施.采用Voronoi图自顶向下切割空域的方法具有自动保证扇区凸性、连通性和压缩性的特性,但计算时间过长.根据航迹状态计算工作负荷,构建了Voronoi图自顶向下切割空域模型,设计了动态步长蚁群搜索算法.测试结果表明,在太原高空划分成4个扇区的情况下,与MC-C...     

基于仿真优化的临时航线动态规划北大核心

为实现空域的灵活使用,对目标空域内军方允许使用的临时航线的动态规划与优化方法进行研究,提出全空域与机场模型(TAAM)和改进离散粒子群优化算法(DPSO)相结合的仿真优化方法。首先,利用TAAM模型构建以最小管制员工作负荷和最低飞行成本为目标的临时航线规划模型;采用组合赋权法和规范化处理确定多目标函数的权重;重新定义DPSO算法的运算规则实现算法改进。以上海部分扇区航路航线的仿真运行数据为例,管制员工作负荷和飞行成本分别下降了13.64%和9.08%。结果表明,上述方法能够有效降低管制员工作负荷和飞行成本,为航班计划的编订提供参考。     

基于概率统计的空域容量评估模型研究

利用概率统计的方法分析研究空域容量的评估问题,从理论上建立估计空域容量的数学模型与方法,建模过程考虑了飞行规则、管制员的能力,空管有关间隔规定,以及机型混杂等多种因素的影响,可分别计算航路、交叉点及空域的容量.在该模型的基础上,设计开发空域容量评估系统,对空域的理论容量进行评估,并利用该系统对某空域容量进行了计算,实际数据证明该模型具有一定的可行性.     

空中交通管制员负荷评估系统的设计

讨论了民航空中交通管制（ATC）工具软件——管制员工作负荷评估系统的实现方法：通过从电报、雷达和基础数据库中获取的航班数据,计算出机场附近各空域中的航班数量和航班位置,以及航班之间的时间间隔,根据以上参数计算管制员的工作强度。并以图形的方式提供给管理人员。     

考虑随机因素的多航段航路容量模型研究

为提高空管信息系统中航路容量评估计算的可信度,在分析原有航路容量模型的基础之上,考虑输入航路对航段容量的影响,根据输入航路最好和最坏两种情况的影响重新建立容量模型.使输入航路成为主航段容量的影响因素之一,同时,引入天气情况、飞行员技术水平、管制员管制水平等影响因素建立多航段航路容量模型.增强了航路容量模型的实用性,对空管信息系统中航路容量评估的建模提供一定参考价值.     

基于云计算的多因素电力负荷坏数据自动检测方法

电力负荷坏数据对电网具有严重的破坏性,为了提高对电力负荷坏数据的检测能力,提出基于云计算的多因素电力负荷坏数据自动检测方法。采用云计算模型进行多因素电力负荷坏数据的分布式重组和集成运算,构建多因素电力负荷坏数据的云网格分布模型,在云网格空间中采用主成分特征分析方法进行多因素电力负荷坏数据特征检测,在双极型直流配电网中实现对多因素电力负荷坏数据的共模分量计算,提取电力负荷坏数据的能量谱特征量,根据负荷用电特性、潮流分布及其容量等参数,实现对多因素电力负荷坏数据的特征检测。仿真结果表明,采用该方法进行多因素电力负荷坏数据检测的自动性较好,检测准确率较高。     

一种基于GeoHash的同覆盖扇区高效判定算法

随着移动通信技术的发展,移动用户的数量与日俱增,相继出现高业务量区域、高校热点场景区域和景区突发高用户数区域,容量不足问题日益凸显。需要实施负载均衡方案解决容量问题,其中同覆盖扇区的判定是首要任务。传统算法采取遍历小区,两两小区比对距离、方位角等方式计算,当小区数据级较大时,计算效率较低且浪费硬件资源。为解决此问题,基于GeoHash模型提出了一种高效同覆盖扇区判定算法。该算法首先对小区及周边九宫格进行GeoHash编码预处理,之后对小区进行GeoHash码聚类,最终通过同聚类中的小区互相比对得到判定结果。经对比实验验证,针对百万级别的小区,算法较传统算法提高效率93倍,且保证了计算的准确性,可以满足快速计算同覆盖扇区需求。     

语音集中监控系统在中南地区的应用

中南语音集中监控系统属于三中心项目其中一项工程,旨在将中南地区所有对空席位的语音信号加以处理,并送到运行管理中心进行统计分析。进而帮助管制运行管理合理调配管制资源和管制员的工作时间,使航班流量与管制员工作达到平衡,为管制运行工作提供量化的、科学的辅助决策手段。     

爱立信SGSN3．0CPU负荷与容量分析

由于爱立信厂家未能提供用户模型、设备配置和SGSN实际容量之间的内在关系解释以及系统CPU负荷、SGSN实际容量的计算方法,为此,本文主要通过对现网数据进行计算及研究,建立一套行之有效的容量分析、监控预警体系来解决这一问题。     

Resource pool management: Reactive versus proactive or let’s be friends

The consolidation of multiple workloads and servers enables the efficient use of server and power resources in shared resource pools. We employ a trace-based workload placement controller that uses historical information to periodically and proactively reassign workloads to servers subject to their quality of service objectives. A reactive migration controller is introduced that detects server overload and underload conditions. It initiates the migration of workloads when the demand for resources exceeds supply. Furthermore, it dynamically adds and removes servers to maintain a balance of supply and demand for capacity while minimizing power usage. A host load simulation environment is used to evaluate several different management policies for the controllers in a time effective manner. A case study involving three months of data for 138 SAP applications compares three integrated controller approaches with the use of each controller separately. The study considers trade-offs between: (i) required capacity and power usage, (ii) resource access quality of service for CPU and memory resources, and (iii) the number of migrations. Our study sheds light on the question of whether a reactive controller or proactive workload placement controller alone is adequate for resource pool management. The results show that the most tightly integrated controller approach offers the best results in terms of capacity and quality but requires more migrations per hour than the other strategies.     

基于BAS-BP模型的新能源汽车充电站相似日负荷预测

现代社会新能源汽车的利用率越来越高,很多城市都开始推广新能源汽车,政府也开始重视新能源汽车的发展。大规模使用新能源汽车可以有效地降低普通汽车尾气对大气的污染,减少了雾霾的产生,从而达到保护环境的目的。但是,大规模使用新能源汽车会增加充电站的负荷,进而造成配电网局部过负荷,加重了电力部门调度的工作量。因此,对于整个配电网来说,对短期新能源汽车充电站的负荷的预测是很有必要的。提出一种基于CEEMDAN分解与BAS-BP组合的模型对相似日新能源汽车充电站进行负荷预测,此方法根据分解出来的各个IMF数据中不同的特点分别对数据进行相应预测最后叠加起来。利用新能源汽车充电站所给的相似日历史数据作为输入参数进行训练所建立的模型来预测次日的负荷量。该组合模型在减小预测误差方面有所改进,研究的问题有一定应用价值。     

Modeling and predicting mental workload in en route air traffic control: critical review and broader implications

OBJECTIVE: We perform a critical review of research on mental workload in en route air traffic control (ATC). We present a model of operator strategic behavior and workload management through which workload can be predicted within ATC and other complex work systems. BACKGROUND: Air traffic volume is increasing worldwide. If air traffic management organizations are to meet future demand safely, better models of controller workload are needed. METHOD: We present the theoretical model and then review investigations of how effectively traffic factors, airspace factors, and operational constraints predict controller workload. RESULTS: Although task demand has a strong relationship with workload, evidence suggests that the relationship depends on the capacity of the controllers to select priorities, manage their cognitive resources, and regulate their own performance. We review research on strategies employed by controllers to minimize the control activity and information-processing requirements of control tasks. CONCLUSION: Controller workload will not be effectively modeled until controllers' strategies for regulating the cognitive impact of task demand have been modeled. APPLICATION: Actual and potential applications of our conclusions include a reorientation of workload modeling in complex work systems to capture the dynamic and adaptive nature of the operator's work. Models based around workload regulation may be more useful in helping management organizations adapt to future control regimens in complex work systems.     

分布式入侵检测中基于能力与负载的数据分割算法

针对高速网络环境下分布式入侵检测中海量数据并行检测处理的效率和检测率问题,提出一种基于能力与负载的数据分割算法。该算法依据采集到的集群内各数据分析节点的系统性能指标及运行状态,评估节点的数据处理能力与负载程度。基于节点的能力与负载适应因子,权衡节点在集群中检测和分析数据能力的权重,实现海量数据在集群内各数据分析节点间的动态数据分割,为节点分配适应其能力与实时负载的数据粒度。仿真测试结果表明,该算法具有较好的负载均衡性,降低了系统的检测时间,提高了数据并行处理的效率和检测率。     

Objective Job Difficulty,Behavioural Response,and Sector Characteristics in Air Route Traffic Control Centres∗

Abstract

Two thousand observations on 47 radar sectors in Boston and New York were used to determine the principal behavioural stressors in the air traffic control environment. Predictor variables included peak traffic. mean airspeed, sector area, sector type, radio-communication time, and theoretically derived control load factors.

Expert observers rated the degree of activity and behavioural arousal of ATCs working the 47 radar sectors at the same time the objective measures were made. These ‘pace’ ratings were significantly related to peak traffic count and duration of radio-communications.

The control load factors were not related to behavioural responses. Statistical analyses indicated several refinements for the definition and measurement of the control load factors, For example, airspace control load was reliably estimated by sector type and number of transitioning planes, while co-ordination control load was most appropriately estimated by duration of radio-communications

These results suggested that estimations of workload may be made by a relatively few objective measures, and that at least one estimate of individual's behavioural responses, i.e.. pace ratings, can be predicted by peak traffic counts.     

空间站载荷转移机构机器人的力加载控制方法

针对机器人在空间站载荷转移机构力加载过程中,由于展开完成后的载荷转移机构在力的方向上发生变形,导致机器人力控制系统难以保持稳定、加载精度不足或调节时间过长的问题,提出了自适应调整导纳控制器参数的策略．首先,根据导纳控制理论建立力与位移的关系,初步提出了基于直角坐标系的力跟随/力加载控制器;然后,根据加载实验数据,采用最小二乘法对载荷转移机构模型进行参数辨识,建立机器人特定工作空间的力与位置关系;最后,通过自适应调整导纳控制器参数使机器人动力学模型与载荷转移机构的动力学模型近似匹配,实现机器人对展开完成后的载荷转移机构末端的空间力实时加载．实验得出机器人对载荷转移机构位置跟随偏差不超过0.1 mm,加载力误差不超过1%．仿真结果表明,该机器人满足精度要求,为载荷转移机构提供了较为真实的等效空间载荷．     

Approaches to team performance assessment: a comparison of self-assessment reports and behavioral observer scales

Human factors research popularly employs perception-based techniques to investigate team performance and its dependency to cognitive processes. Such studies frequently rely upon either observer-based or self-assessment techniques to collect data. In this study, we examined behavioral observer ratings and self-assessment ratings for measuring team performance in virtual teams, with team performance regarded as a combination of task outcome and team cognition. Juxtaposing self-assessments and observer ratings from a quasi-experiment comparing team performance rating techniques reveals that they indeed produce overall similar results, with both singling out teamwork effectiveness ratings as the strongest contributor to overall team performance. However, the comparisons show remarkably low correlation on individual questionnaire items. The most striking difference is that the team members’ self-assessments of workload are lower than the corresponding observer ratings. In particular, the self-assessments do not correlate at all with overall team performance, whereas the observers’ workload ratings are more consistent with contemporary research that suggests a strong correlation between workload and team performance, suggesting that observer-based techniques are more reliable than self-assessments for assessing workload. For other ratings, the results show that the two techniques are fairly equal, suggesting that the choice between methods to employ can be deferred to other considerations such as obtrusiveness, accessibility, and resource availability.

     

Measurements of team workload: A time pressure and scenario complexity study for maritime operation tasks

Workload is a critical factor influencing team performance in complex systems. There remains no consensus on the selection of team workload measures. Through an experiment based on simulated maritime operation tasks, team workload was manipulated by time pressure and scenario complexity to investigate the responses of three categories (subjective, performance-based, and physiological) of potential team workload measurements. The results show that time pressure had significant effects on all the three categories of measurements, especially on subjective indicators, miss rate, completion rate, operation accuracy, and eye movements. Significant main effects of scenario complexity on subjective team workload and the selected team performance measurements were also found, such as response latent time, miss rate, completion rate, and operation accuracy. Physiological measurements may not be sensitive for measuring team workload when scenario complexity serves as a major influencing factor of team workload.