Application of Neural Networks for the Safety and Performance Evaluations of Infrastructure Systems

神经网络在基础设施系统安全和性能评估中的应用

• 批准号: 9402049
• 负责人: Karen Chou
• 金额: $ 4.99万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-08-15 至 1996-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9402049&HistoricalAwards=false
• 关键词: Application; Neural; Networks; Safety; Performance

9402049 Chou The neural network's capability of making reasonable response (output) even when it was presented with incomplete, noisy or previously unseen input has significant impact in engineering applications. Many times, due to physical or environmental limitations such as after a natural disaster, not all forms or types of data are collected for safety analysis. In this situation, tradition reliability analysis could be halted, terminated or greatly compromised. In addition, neural network accepts relationships between input and response that are deterministic, probabilistic or fuzzy. The Career Advancement Award for Women Scientists and Engineers provides the Investigator an opportunity to expand her current research area of structural safety utilizing probabilistic, statistical and fuzzy set theory to civil engineering, particularly structural engineering. Neural network is an artificial intelligence tool that has shown to be more flexible than expert systems. From studies performed in other engineering disciplines, they show great potential that the concept is applicable to civil engineering problems as well. ***

9402049 Chou 即使在输入不完整、有噪声或以前未见过的输入时，神经网络也能做出合理的响应（输出），这对工程应用具有重大影响。很多时候，由于物理或环境限制（例如自然灾害后），并非所有形式或类型的数据都会被收集用于安全分析。在这种情况下，传统的可靠性分析可能会停止、终止或受到极大影响。此外，神经网络接受输入和响应之间的确定性、概率性或模糊关系。女科学家和工程师职业进步奖为研究者提供了一个机会，利用概率、统计和模糊集理论将其当前的结构安全研究领域扩展到土木工程，特别是结构工程。神经网络是一种人工智能工具，已被证明比专家系统更灵活。从其他工程学科进行的研究来看，他们表明该概念也适用于土木工程问题的巨大潜力。 ***