Katrina SGER: Dynamic Programming-based Health Monitoring and Prognostics for Levee and Communication Infrastructures

Katrina SGER：基于动态规划的堤坝和通信基础设施健康监测和预测

• 批准号: 0633769
• 负责人: Jagannathan Sarangapani
• 金额: --
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2008-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0633769&HistoricalAwards=false
• 关键词: Katrina; SGER; Dynamic; Programming; based

AbstractProposal Number: 0633769Proposal Title: Katrina SGER: Dynamic Programming-based Health Monitoring and Prognostics for Levee and Communication InfrastructuresPI Name: Sarangapani, JagannathanPI Institution: University of Missouri-RollaIntellectual Merit: This PI will use novel methods, based upon computational intelligence and learning, to develop a system to couple health monitoring sensors and wireless communications, to provide real-time assessment of the levee system in New Orleans and similar areas. The integration of these advanced technologies is a unique and challenging intellectual task high risk but high potential. Within the area of computational intelligence, it will rely heavily on adaptive dynamic programming with neural networks, an important emerging priority within the PCAN program of the ECS Division. (See www.eas.asu.edu/~nsfadp.) Broader impacts: This SGER is part of a group of SGER proposals funded by special funds in fiscal year 2006, set aside for projects which may leverage unique capabilities of the NSF research community to try to benefit the victims of Katrina. Because the state of the levees is the most important single piece of information that the people in that area need to know about and anticipate better, this project directly addresses their needs.

摘要提案编号：0633769提案标题：Katrina SGER：基于动态规划的堤防和通信基础设施健康监测与预测项目名称：Sarangapani， JagannathanPI机构：University of missouri - rolli该项目将使用基于计算智能和学习的新方法，开发一个将健康监测传感器和无线通信结合起来的系统，为新奥尔良和类似地区的堤坝系统提供实时评估。这些先进技术的集成是一项独特而具有挑战性的智力任务，风险高，潜力大。在计算智能领域，它将严重依赖于神经网络的自适应动态规划，这是ECS部门PCAN计划中一个重要的新兴优先事项。（见www.eas.asu.edu/~nsfadp）更广泛的影响：这是2006财政年度由特别基金资助的一组特别研究计划的一部分，专门用于可能利用国家科学基金会研究界的独特能力来努力使卡特里娜飓风的受害者受益的项目。由于堤坝的状态是该地区的人们需要了解和更好地预测的最重要的信息，因此该项目直接满足了他们的需求。