基于遗传编程技术的强地震动参数预测方法OA北大核心CSTPCD

Based on NGA database and using genetic programming techniques,we give a set of predic-tion equations for PGA,PGV and PGD.On the basis of the explicit prediction formula,the reliability test and model comparison are carried out by establishing the correlation between ground motion pa-rameters and key seismological parameters such as magnitude,fault distance,fault mechanism,and site shear wave velocity within 30 meters.The results show that:1)Compared with the traditional decay relation-like prediction equations based on nonlinear regression techniques,genetic program-ming techniques do not need to specify the equation form of the decay relation,can model the complex behaviors of PGA,PGV and PGD,and give explicit formulas to meet engineering needs.2)Compared with the Campbell-Bozorgnia attenuation relationship,the prediction effect of PGA and PGV based on the genetic programming techniques is slightly better;the RMSE and MAE of the PGD prediction model are 5.47 and 1.64,respectively,which are significantly smaller than those of the Campbell-Bo-zorgnia model,which are 45.98 and 4.61.3)The obtained ground motion prediction equations are characterized by magnitude effect,site amplification effect,and saturation effect of near-field large earthquakes,but fail to reflect the soft-soil damping effect,and the maximum site amplification coeffi-cients of PGA,PGV and PGD are about 1.42,2.53 and 2.64.