Application of machine learning method in bridge health monitoring
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[1] Lieping Ye,et al. Damage identification of reinforced concrete beams , 2011, 2011 Second International Conference on Mechanic Automation and Control Engineering.
[2] Xiaomin Wang,et al. The Application of BP Neural Network in Cable-Stayed Bridge Construction Monitoring , 2010, 2010 International Conference on Computational and Information Sciences.
[3] Kurt Hornik,et al. Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks , 1990, Neural Networks.
[4] Ruizi Wang. Integrated health prediction of bridge systems using dynamic object oriented Bayesian networks (DOOBNS) , 2012 .
[5] Lin Wang,et al. Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm , 2016 .
[6] Akira Mita,et al. Damage Detection Method Using Support Vector Machine and First Three Natural Frequencies for Shear Structures , 2013 .
[7] Sai Ji,et al. Structural Damage Detection using Wireless Intelligent Sensor Networks , 2012 .
[8] Mehdi Nikoo,et al. Principal Component Analysis combined with a Self Organization Feature Map to determine the pull-off adhesion between concrete layers , 2015 .
[9] K. Worden,et al. The application of machine learning to structural health monitoring , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.
[10] Arturo E. Schultz,et al. Bridge Health Monitoring and Inspections – A Survey of Methods , 2009 .
[11] Zan Xinwu. Missing Data Imputation in Bridge Health Monitoring System Based on the Support Vector Machine , 2012 .
[12] Shuai Guo,et al. Bridge Health Evaluation System based on the Optimal BP Neural Network , 2014 .
[13] Ming L. Wang,et al. Support vector machine for abnormality detection on a cable-stayed bridge , 2010, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.
[14] Siddharth Sharma,et al. Application of Support Vector Machines for Damage Detection in Structures , 2009 .
[15] Gyuhae Park,et al. Structural Health Monitoring With Autoregressive Support Vector Machines , 2009 .
[16] S. Arangio,et al. Neural Network-Based Techniques for Damage Identification of Bridges: A Review of Recent Advances , 2013 .
[17] Dustin Boswell,et al. Introduction to Support Vector Machines , 2002 .
[18] W. T. Yeung,et al. Damage detection in bridges using neural networks for pattern recognition of vibration signatures , 2005 .
[19] Zhibin Lin,et al. Data-driven support vector machine with optimization techniques for structural health monitoring and damage detection , 2017, KSCE Journal of Civil Engineering.
[20] Xiao-li Lu,et al. Towards an Abnormal Bridge Location Identification Method Based on Novelty Detection Technique , 2016 .
[21] Mannur J. Sundaresan,et al. A Study of Machine Learning Techniques for Detecting and Classifying Structural Damage , 2015 .
[22] Luis Eduardo Mujica,et al. Damage classification in structural health monitoring using principal component analysis and self‐organizing maps , 2013 .
[23] Victor Giurgiutiu,et al. Comparative study of neural network damage detection from a statistical set of electro-mechanical impedance spectra , 2003, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.
[24] Fu Yu-mei. Missing Data Imputation in Bridge Health Monitoring System base on Hybrid Model of Neural Network and Time Series , 2011 .