Design and Analysis of Algorithms for Structured Nonlinear Problems

结构化非线性问题的算法设计与分析

• 批准号: RGPIN-2015-05481
• 负责人: Corless, Robert
• 金额: $ 1.75万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=590457
• 关键词: Design; Analysis; Algorithms; Structured; Nonlinear

Modern science relies very heavily on computer simulation of scenarios that behave according to theoretical models. If the simulations perform as expected in the “testing” phase, then confidence in the theory underlying the model is bolstered. If the simulations manage to predict real-world behavior, especially if it is surprising (or might potentially cost lives or money if unanticipated) then they are of social benefit, not just academic importance.  But carrying out such simulations on a computer often involves solving a potentially large number of nonlinear equations. Doing so reliably and efficiently enough that predictions can be made in real time can be (depending on the subject area) extremely challenging. This project aims at producing new algorithms to make such solutions both more reliable and more efficient.

现代科学在很大程度上依赖于计算机模拟，这些场景根据理论上的模型行为。如果模拟在“测试”阶段按预期执行，则对模型基础理论的信心得到加强。如果模拟设法预测了现实世界的行为，尤其是如果令人惊讶（或者如果意外，可能会损失生命或金钱），那么它们具有社会利益，而不仅仅是学术上的重要性。但是在计算机上进行此类模拟通常涉及解决潜在的大量非线性方程。如此可靠，有效地做到这一点，可以实时做出预测（取决于主题领域）极为挑战。该项目旨在生产新算法，以使此类解决方案更加可靠，更有效。