CGV: Large: Collaborative Research: Modeling, Display, and Understanding Uncertainty in Simulations for Policy Decision Making

CGV：大型：协作研究：建模、显示和理解政策决策模拟中的不确定性

• 批准号: 1540469
• 负责人: Michael Lindell
• 金额: $ 28.11万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-31 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1540469&HistoricalAwards=false
• 关键词: CGV; Large; Collaborative; Research; Modeling

The goal of this collaborative project (1212806, Ross T. Whitaker, University of Utah; 1212501, Donald H. House, Clemson University; 1212577, Mary Hegarty, University of California-Santa Barbara; 1212790/1540469, Michael K. Lindell, Texas A&M University/University of Washington) is to establish the computational and cognitive foundations for capturing and conveying the uncertainty associated with predictive simulations, so that software tools for visualizing these forecasts can accurately and effectively present this information about to a wide range of users. Three demonstration applications are closely integrated into the research plan: one in air quality management, a second in wildfire hazard management, and a third in hurricane evacuation management. This project is the first large-scale effort to consider the visualization of uncertainty in a systematic, end-to-end manner, with the goal of developing a general set of principles as well as a set of tools for accurately and effectively conveying the appropriate level of uncertainties for a range of decision-making processes of national importance.The primary impact of this work will be methods and tools for conveying the results of predictive simulations and their associated uncertainties, resulting in better informed public policy decisions in situations that rely on such forecasts. Scientific contributions are expected in the areas of simulation and uncertainty quantification, visualization, perception and cognition, and decision making in the presence of uncertainty. Results will be broadly disseminated in a variety of ways across a wide range of academic disciplines and application areas, and will be available at the project Web site (http://visunc.sci.utah.edu). The multidisciplinary nature of the research and the close integration of the participating research groups will provide a unique educational environment for graduate students and other trainees, while also broadening the participation in computer science beyond traditional boundaries.

这个合作项目的目标（1212806，犹他大学罗斯·惠特克； 1212501，克莱姆森大学唐纳德·H·豪斯； 1212577； 1212577，玛丽·黑尔蒂，加利福尼亚大学圣塔芭芭拉大学； 1212790/1540469 A＆M大学/华盛顿大学）将建立用于捕获和传达与预测模拟相关的不确定性的计算和认知基础，以便可视化这些预测的软件工具可以准确有效地向广泛的用户提供有关此信息。三个演示申请紧密整合到研究计划中：一项是空气质量管理，第二个野火危害管理，第三个是飓风疏散管理。该项目是以系统的，端到端的方式考虑不确定性的第一个大规模努力，其目的是制定一系列一般原则以及一组工具，用于准确有效地传达适当的适当对于一系列国家重要性的决策过程的不确定性水平。这项工作的主要影响将是传达预测性模拟及其相关不确定性结果的方法和工具，从而在依靠依赖的情况下做出更好的公共政策决策这样的预测。 在仿真和不确定性定量，可视化，感知和认知以及在不确定性存在下的决策领域中，预计科学贡献。结果将以各种方式在广泛的学科和应用领域中进行广泛传播，并将在项目网站（http://visunc.sci.utah.edu）上提供。 研究小组的研究的多学科性质以及参与研究小组的密切整合将为研究生和其他学员提供独特的教育环境，同时还将计算机科学的参与扩大到传统界限之外。