Adaptive neural networks for model updating of structures Youfreesexcam com


25-Dec-2017 10:11

adaptive neural networks for model updating of structures-23

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Data-driven approaches attempt to derive models directly from routinely collecting condition-monitored (CM) data instead of building models based on comprehensive system physics and human expertise.

They are built based on historical records and produce prediction outputs directly in terms of CM data [16], including the DP methods based on wavelet artificial neural network [17], Bayesian framework [18–20], Kalman estimator [21, 22], fuzzy theory [23], and probability analysis [24, 25].

The results show that the predicted results of the damage prognosis method and the measured results are very well consistent, and the maximum error is less than 5%.

The displacement has a slight increase and seasonal characters in the critical section of mid span, but the strain will increase distinctly.Design and control of micro robots have been one of the interesting fields in robotics in recent years.