CISE Research Instrumentation: Instrumentation for Experimental Research in Machine Learning, Molecular Dynamics, Probabilistic Reasoning, and Software Maintenance

CISE 研究仪器：用于机器学习、分子动力学、概率推理和软件维护实验研究的仪器

• 批准号: 9818414
• 负责人: Thomas Dietterich
• 金额: $ 8.7万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-02-01 至 2002-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9818414&HistoricalAwards=false
• 关键词: CISE; Research; Instrumentation; Experimental; Machine

9818414Dietterich, Thomas G.Rudd, Walter G.Oregon State UniversityInstrumentation for Research in Machine Learning, Molecular Dynamics, Probabilistic Reasoning, and Software MaintenanceThis research instrumentation enables research projects in:- Experimental Machine Learning Research,- Accelerating Simulations in the Time Dimension,- Probabilistic Methods in Dynamic Environments, and - Experimentation with Program-Analysis-Based Systems Maintenance and Testing Techniques.To support the aforementioned projects, this award contributes to the purchase of dual-processor Pentium II computers and associated networking hardware by the Department of Computer Science at Oregon State University. The equipment will support experimental research on four projects. In the first project, machine learning tools will be developed for complex problems such as image analysis and language processing. These tools will help solve related problems faster and with higher accuracy. The second project concentrates in developing faster algorithms for complex particle simulations. These algorithms will make it possible to understand and predict the behavior of chemical compounds in manufacturing (e.g., adhesives, aircraft parts) and environmental cleanup (e.g. contaminant flow in soils). The third project studies improved techniques for reasoning under uncertainty. These techniques allow building faster and more accurate systems for real-time diagnosis and repair of complex systems such as automobiles, spacecraft, and factories. The last project concentrates in developing and applying new methods and tools for program analysis to improve the testing and maintenance of complex software systems. These tools are expected to reduce the cost and improve the reliability of new and existing software systems.

9818414 Dietterich，托马斯G.Rudd，Walter G.俄勒冈州州立大学机器学习、分子动力学、概率推理和软件维护研究仪器该研究仪器支持以下领域的研究项目：- 实验机器学习研究，-加速时间维度的模拟，-动态环境中的概率方法，以及-基于程序分析的系统维护和测试技术的实验。为了支持上述项目，该奖项有助于俄勒冈州州立大学计算机科学系购买双处理器奔腾II计算机和相关网络硬件。 该设备将支持四个项目的实验研究。 在第一个项目中，机器学习工具将被开发用于图像分析和语言处理等复杂问题。 这些工具将有助于更快、更准确地解决相关问题。 第二个项目集中于开发复杂粒子模拟的更快算法。 这些算法将使理解和预测化学化合物在制造中的行为成为可能（例如，粘合剂、飞机部件）和环境清理（例如土壤中的污染物流动）。 第三个项目研究不确定性下推理的改进技术。 这些技术允许构建更快，更准确的系统，用于实时诊断和修复复杂系统，如汽车，航天器和工厂。 最后一个项目集中在开发和应用新的方法和工具进行程序分析，以提高测试和维护复杂的软件系统。 预计这些工具将降低成本，提高新的和现有的软件系统的可靠性。