Datasets:

JasonXF
/

SeFNO

model stringclasses 6 values	checkpoint stringclasses 6 values	numel int64 7.36M 9.44M	numel_m float64 7.36 9.44	real_params int64 7.36M 16.9M	real_params_m float64 7.36 16.9	trainable int64 7.36M 9.44M	mse float64 0.01 0.74	rmse float64 0.1 0.86	mae float64 0.04 0.53	r2 float64 0.05 0.99	pfa_mse_g2 float64 0 0.06	pfa_rmse_g float64 0.02 0.25	pfa_mae_g float64 0.01 0.21	pfa_r2 float64 -1.29 0.99	loss float64 0.01 0.74	spectral_log_mse float64 0.19 1.26	high_freq_log_mse float64 0.22 1.09	latency_ms_per_sample float64 0.07 1.05
MLP	/data/home/jason/Seismic-FNO/6-code/O1-baseline-comparison/results/runs/MLP/checkpoints/MLP_best.pt	9,444,352	9.444352	9,444,352	9.444352	9,444,352	0.741989	0.861388	0.530324	0.0462	0.060708	0.246389	0.210652	-1.287023	0.742131	1.255193	1.09096	0.074924
BiLSTM	/data/home/jason/Seismic-FNO/6-code/O1-baseline-comparison/results/runs/BiLSTM/checkpoints/BiLSTM_best.pt	8,410,113	8.410113	8,410,113	8.410113	8,410,113	0.009919	0.099593	0.043221	0.98725	0.00033	0.018168	0.010825	0.987565	0.009924	0.185284	0.222229	1.04947
ResCNN1D	/data/home/jason/Seismic-FNO/6-code/O1-baseline-comparison/results/runs/ResCNN1D/checkpoints/ResCNN1D_best.pt	7,355,137	7.355137	7,355,137	7.355137	7,355,137	0.148097	0.384834	0.217985	0.809627	0.002988	0.054662	0.041175	0.887438	0.148206	0.484007	0.53389	0.606539
UNet1D	/data/home/jason/Seismic-FNO/6-code/O1-baseline-comparison/results/runs/UNet1D/checkpoints/UNet1D_best.pt	7,848,321	7.848321	7,848,321	7.848321	7,848,321	0.215748	0.464487	0.271709	0.722664	0.011309	0.106342	0.08679	0.57397	0.215788	0.588036	0.632896	0.095814
Transformer	/data/home/jason/Seismic-FNO/6-code/O1-baseline-comparison/results/runs/Transformer/checkpoints/Transformer_best.pt	7,957,775	7.957775	7,957,775	7.957775	7,957,775	0.02139	0.146254	0.066038	0.972503	0.000533	0.023096	0.014949	0.979904	0.021471	0.325037	0.390727	0.105781
FNO-Large	6-code/O1-baseline-comparison/results/runs/FNO-Large-bs64/checkpoints/FNO-Large-bs64_best.pt	8,505,793	8.505793	16,927,169	16.927169	8,505,793	0.044881	0.211851	0.105011	0.942307	0.001088	0.032981	0.020488	0.959021	0.044962	0.341642	0.397793	0.107898

KNET Seismic Ground Motion & Building Response Dataset (MDOF)

Ground motion records from the K-NET strong-motion network (Japan), paired with numerically simulated floor acceleration responses for 250 multi-degree-of-freedom (MDOF) shear-building configurations. Used to train and evaluate Fourier Neural Operator (FNO) models for seismic structural response prediction.

Dataset Summary

Property	Value
Ground motion records	3,474 (K-NET)
Amplitude scale factors per GM	57
Building configurations	250 MDOF shear buildings
Signal length	3,000 time steps (60 s @ 50 Hz)
GM file format	HDF5 (`.h5`)
Building response format	HDF5 (`.h5`), one file per building

File Structure

MDOF/
├── All_GMs/
│   └── GMs_knet_3474_AF_57.h5        # Ground motion inputs
└── knet-250/
    └── Data/
        └── fno/
            ├── Blg_F6_18m_IM7_st0.h5.h5       # Floor acc. response

Ground Motion File (`GMs_knet_3474_AF_57.h5`)

Each entry stores the scaled acceleration time series for one GM × scale-factor combination.

HDF5 Key pattern	Shape	Description
`gm_{i}/af_{j}/data`	`(3000,)`	Scaled acceleration (m/s²), 50 Hz
`gm_{i}/af_{j}/pga`	scalar	Peak ground acceleration (m/s²)
`gm_{i}/metadata`	attrs	Station, event, magnitude, etc.

Building Response Files (`Blg_F6_18m_IM7_st0.h5.h5`)

Each file stores the simulated structural response for all GM × scale combinations for one building.

HDF5 Key	Shape	Description
`response/gm_{i}/af_{j}/floor_acc`	`(n_floors, 3000)`	Floor acceleration (m/s²)
`building/attributes`	attrs	Number of floors, periods, damping, etc.
`building/damage_state/gm_{i}/af_{j}`	scalar int	HAZUS damage state (0–4)