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Table 7 Standard deviation of model residuals for various GRNN models implying the initial, actual frequency amplification factors (RP, NP, TP cases, last three columns) for various combinations of site parameters

From: Deriving amplification factors from simple site parameters using generalized regression neural networks: implications for relevant site proxies

Number of parameters

Considered site parameters

Error (RP)

Error (NP)

Error (TP)

All (6)

Depth + f 0 + V sm + C v +V s30 + V bedrock

0.0011

0.0032

0.0053

3 (best triplet)

f 0 + C v  + V s30

0.0079

0.0079

0.0118

2 (best pair)

f 0 + C v

0.0251

0.0233

0.0278

2 (convenient pair)

f 0 + V s30

0.0782

0.0382

0.0339

1 (best)

C v

0.0725

0.0652

0.0622

1 (usual)

V s30

0.1038

0.0715

0.0733

1

f 0

0.099

0.0678

0.0563

Overall initial variability term \(\sigma_{\text{m}} \left( \theta \right)\)

0.1178

0.0846

0.0896