贝叶斯概率
计算机科学
变阶贝叶斯网络
结构健康监测
贝叶斯推理
桥(图论)
贝叶斯因子
贝叶斯定理
数据挖掘
工程类
人工智能
结构工程
医学
内科学
标识
DOI:10.1177/1475921716688166
摘要
Bridge monitoring systems produce a large amount of data, including uniform and non-uniform sampled data in the long-term service periods; the proper handling of these data is one of the main difficulties in structural health monitoring. To properly predict structural non-uniform extreme stress and deal with the uncertainties of the monitored data, the objectives of this article are to present (a) Bayesian dynamic linear models about non-uniform extreme stress, (b) monitoring mechanism about the Bayesian dynamic linear models based on single and cumulative Bayes’ factors, and (c) an effective use of the Bayesian dynamic linear models to incorporate the dynamic monitored data into structural non-uniform extreme stress prediction. The proposed models and procedure are applied to the monitored data obtained from the I-39 Northbound Bridge over the Wisconsin River in Wausau, Wisconsin, USA.
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