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Fig 1.

The schematic of the monitoring equipment layout of the bridge.

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Fig 2.

The dimension marking for the schematic diagram.

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Fig 3.

Measured mean wind speed time series curve.

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Fig 4.

The rose chart of mean wind direction characteristics.

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Fig 5.

The scatter plot of the correlation between turbulence and mean wind speed for downwind turbulence intensity.

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Fig 6.

The scatter plot of the correlation between turbulence and mean wind speed turbulence intensity in the crosswind direction.

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Fig 7.

The RMS curve of measured vibration response acceleration in each direction.

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Fig 8.

Distribution of partial autocorrelation functions for acceleration in different directions.

(a) Lag order of acceleration in the along the bridge direction; (b) Hysteresis order of acceleration in the transverse direction; (c) Lag order of vertical acceleration; (d) Torsional acceleration hysteresis order.

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Fig 9.

Schematic of one-dimensional causal convolution.

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Fig 10.

Principle schematic of dilated convolution.

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Fig 11.

The structure of the residual connection block.

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Fig 12.

The framework diagram of the bridge wind-vibration response prediction algorithm.

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Fig 13.

The illustration of sliding window for median filtering.

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Fig 14.

Correlation coefficients between wind characteristic parameters and RMS values of wind vibration response of bridges.

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Table 1.

The range of hyperparameters and results.

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Table 2.

Comparison of prediction errors of different.

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Fig 15.

Acceleration prediction results of different models along the bridge acceleration.

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Fig 16.

Acceleration prediction results of different models in transverse acceleration.

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Fig 17.

Acceleration prediction results of different models in vertical acceleration.

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Fig 18.

Acceleration prediction results of different models in torsional acceleration.

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Table 3.

Comparison of training time for different algorithms (Unit: second).

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Fig 19.

Comparison of training time.

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Table 4.

Comparison of forecast time for different algorithms (Unit: second).

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Table 5.

Comparison of inference speed for different algorithms (Unit: ms/patch).

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Table 6.

The p-value result of paired t-tests for different prediction algorithms(Alpha level of α = 0.05).

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Table 7.

Statistical characteristics of the four sets of wind data.

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Fig 20.

Wind speed (left) and wind rose plots (right) were used for sensitivity analysis of raw data for group a.

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Fig 21.

Wind speed (left) and wind rose plots (right) were used for sensitivity analysis of raw data for group b.

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Fig 22.

Wind speed (left) and wind rose plots (right) were used for sensitivity analysis of raw data for group c.

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Fig 23.

Wind speed (left) and wind rose plots (right) were used for sensitivity analysis of raw data for group d.

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Table 8.

Sensitivity test results.

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