Generalization capability of neural network models for temperature- frequency correlation using monitoring data

Journal of Structural Engineering

Volumn 135, Issue 10, 2009, Pages 1290-1300

  Ni, Y Q ^a   Zhou, H F ^a   Ko, J M ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Bridges, cable stayed; Correlation; Monitoring; Natural frequency; Neural networks; Temperature effects

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; BAYESIAN REGULARIZATION; BRIDGES, CABLE-STAYED; CORRELATION; CORRELATION MODELS; EARLY STOPPING; ENVIRONMENTAL TEMPERATURE; FREQUENCY CORRELATION; GENERALIZATION CAPABILITY; HIDDEN NODES; LONG TERM MONITORING; MODAL FREQUENCY; MODAL PROPERTIES; MODAL VARIABILITY; NEURAL NETWORK MODEL; PARAMETRIC APPROACH; PREDICTION CAPABILITY; STRUCTURAL DAMAGE DETECTION; TEMPERATURE DATA; TEMPERATURE EFFECTS; TESTING DATA; TRAINING ALGORITHMS; TRAINING DATA; TWO LAYERS; VALIDATION DATA;

BAYESIAN NETWORKS; BRIDGE CABLES; CABLE STAYED BRIDGES; CABLES; COMPUTER NETWORKS; CORRELATION METHODS; DAMAGE DETECTION; NATURAL FREQUENCIES; STRUCTURAL ANALYSIS; TEMPERATURE; THERMAL EFFECTS;

NEURAL NETWORKS;

EID: 70349336497     PISSN: 07339445     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)ST.1943-541X.0000050     Document Type: Article

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