Visually supported reasoning under uncertain conditions: Effects of domain expertise on air traffic risk assessment

This article investigates the impact that domain expertise has on risk assessment when analyzing uncertain geographical and sensor data. The differences between novice and expert air traffic operators were examined taking into account the performance of identifying and classifying threatening targets, the time needed to carry out such classifications, and the confidence reported for each decision. The results show that confidence was significantly higher for the expert group. This was supported by the after-test questionnaire because none of the novice participants reported being more confident with the visualizations of uncertainty provided. No significant differences regarding time and performance were found between the groups, even if experts needed, on average, more time to make a decision. Based on the collected logs, the experienced participants more often accessed the detailed information for each object presented by the tool tip. Both the time taken and the data accessed might indicate that experts had better situation awareness. Finally, the experts reported higher workload values related to performance.     

Special issue introduction: Approaching spatial uncertainty visualization to support reasoning and decision making

While research on uncertainty and decision-making has a long history across several disciplines, recent technological developments compel researchers to rethink how to best address and advance the understanding of how humans reason and make decisions under spatial uncertainty. This introduction presents a visual summary graphic to provide an overview of each article in this special issue. Upon viewing these visual summaries, the reader will find that each of these articles covers different topics in the uncertainty visualization domain, offering complementary research in this field. Extending this body of research and finding new ways to explore how these visualizations may help or hinder the analytical and reasoning process of humans continues to be a necessary step towards designing more effective uncertainty visualizations to support reasoning and decision-making.     

基于支持向量机的抗干扰决策技术

为了应对日益复杂的电磁环境,认知雷达的概念被引入电子战中。认知电子战系统包括认知侦察、认知对抗和认知效能评估3个重要环节。针对认知电子战系统对抗干扰决策技术的需求,为实现自适应的决策抗干扰措施,将支持向量机(SVM)算法运用于抗干扰决策中。仿真结果表明:基于SVM的抗干扰决策技术可以自适应地决策抗干扰措施,进行干扰对抗,该算法完成了认知电子战中的最后的一步,使认知电子战系统实现闭环。     

航空装备视情维修决策研究

航空装备从正常到潜在故障需要经过检测才能知道。本文建立了符合航空装备特点的视情维修决策模型,通过Markov状态分析,以装备的最大可用度为目标函数,确定了基于航空装备的可靠性的检测间隔期和视情维修阈值的求解方法,为航空装备开展视情维修提供了依据,并将所得结论应用于某型飞机的滑油系统进行验证,得出检测次数与装备可用度的关系。     

多目标随机决策分析的IRGSD—FDⅡ方法

本文就多目标随机决策问题,通过引进一种新的解的概念——目标满足度β与约束可行度α协调解,简称(α,β)一协调解。提出了一种决策方法——交互式参考目标满足度与可行度方法Ⅱ(IRGSD—FDⅡ),并讨论了这一方法在研究开发(R&D)项目选择问题中的应用。这一方法的基本步骤包括:替代问题的产生;决策者初始约束可行度α、目标满足度β及目标参考水平q的确定;反映决策者偏好的多属性效用函数的估计;替代目标函数的重新定义和求解;与决策者的对话;最佳(α,β)协调解的获得等等。     

基于多目标决策模型的两栖攻击舰编队编成研究

两栖攻击舰编队编成不能照搬固定的模式,而应根据作战任务和威胁等因素进行合理配置。文章分析了两栖攻击舰编队的作战能力,并在此基础上构建了编成模型的指标体系。运用多目标决策理论,建立了两栖攻击舰编队编成的模型,通过计算得到了针对某作战行动中两栖攻击舰编队的最优编成方案,并将所得到的结果与日常性建制的编队编成进行了比较。