MS04: Probabilistic SHM
Organizers: Profs. Daniele Zonta and Branko Glisic

MS04-01 Two Probabilistic Damage Detection Approaches by B. Glisic, Y. Yao, and D. Sigurdardottir
MS04-02 Prediction of the Failure Time of Civil Infrastructure Systems Using Empirical Failure Model by Y. Zhang and Z. Li
MS04-03 Optimal Topology of Sensor Networks for Management of Infrastructure Systems by C. Malings, M. Memarzadeh, and M. Pozzi
MS04-04 Damage Identification of Benchmark Structure with Unknown Excitations Using Quadratic Sum-Squares Error with AR Model by H.W. Huang and J.N. Yang
MS04-05 Comparison of Statistical Counting Methods in SHM-Based Reliability Assessment of Bridges by X. Wang and Y.Q. Ni
MS04-06 On the Impact of Prior Perception on Bridge Health Diagnosis by C. Cappello, F. Bruschetta, D. Zonta, S. Maestranzi, R. Zandonini, M. Pozzi, B. Glisic, D. Inaudi, and D. Posenato
MS04-07 A Bayesian Optimization Approach for Wind Farm Monitoring and Power Maximization by J. Park and K. H. Law
MS04-08 Data Analysis Approaches for Structural Health Monitoring by F. Necati Catbas
MS04-09 The Need of SHM for Bridge Management and Its Integration into Bridge Management Systems by Eloi Figueiredo
MS04-10 Forecasting Anomalies Using Monitoring Data and Dynamic Bayesian Networks by J.A. Goulet and A. Der Kiureghian
MS04-11 Pavement Macrotexture Estimation Using Principal Component Analysis of Tire Noise by Y. Zhang, J.G. Mcdaniel, and M.L. Wang
MS04-12 Damage Classification Using Support Vector Machines in Guided Wave Structural Health Monitoring by Xiang Li, Daewon Kim, and Yi Zha