Algorithmic Methods in Applied Probability

应用概率中的算法方法

• 批准号: 8600992
• 负责人: Ushio Sumita
• 金额: $ 2.4万
• 依托单位: University of Rochester
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1986
• 资助国家: 美国
• 起止时间: 1986-07-15 至 1987-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8600992&HistoricalAwards=false
• 关键词: Algorithmic; Methods; Applied; Probability

Probability Theory has undergone rapid transformations in recent decades, due largely to the demand by industry and defense to address increasing complete decision problems. Theoretical advances have outstripped computational considerations. The principal investigator will begin to rectify this imbalance by focusing on algorithm methods in applied probability, in particular, by the developing and testing of algorithms based on specific classes of distribution, the structure of processes and for continuum operations via transform methods.

近年来，概率论发生了迅速的转变 几十年来，主要是由于工业和国防的需求，以解决 增加了完整的决策问题。 理论的进步 超越了计算的考虑。 主要研究者 我将开始通过关注算法方法来纠正这种不平衡 在应用概率方面，特别是通过开发和测试 算法基于特定类的分布、结构， 过程和连续操作通过变换方法。