丁佳伟,吕大刚,曹正罡. Clough‑Penzien 功率谱模型参数的识别与统计建模及应用[J].振动工程学报,2023,36(5):1204~1215.[The Clough-Penzien power spectrum of ground motion （C?P spectrum） has clear physical significance, but needs to identify many parameters. The ordinary least squares （OLS） algorithm has shortcomings such as high requirements for the selection of initial values for nonlinear identification of data,,inability to quickly, effectively realize accurate identification of largescale parameters. In this paper, the adaptive weighted particle swarm optimization （AWPSO） algorithm is used to identify the C-P spectral model parameters based on typical ground motion records. The results show that the recognition accuracy of the AWPSO algorithm is improved by at least .% compared with the OLS algorithm,,the computational efficiency has been greatly im? proved. ground motion records are selected from the ground motion record database, grouped according to the site classification standards in the building seismic design code. The AWPSO algorithm is used to identify, count the parameters of the C-P spectrum model of various sites. Using K-S test, A-D test, AIC information criterion, the optimal probability distribution model of each parameter is determined,,the correlation coefficient between each parameter is further calculated,,the joint probability density function of C-P spectral model is established. Using the Latin hypercube sampling method, the statistical sampling CP spectral model of the site is obtained,,the power spectrum of the standard transformation is compared, analyzed. The artificial ground motion synthesis method with iterative correction of the power spectrum is used to generate the artificial seismic record with the site characteristics., The Clough-Penzien power spectrum of ground motion （C?P spectrum） has clear physical significance, but needs to identify many parameters. The ordinary least squares （OLS） algorithm has shortcomings such as high requirements for the selection of initial values for nonlinear identification of data,,inability to quickly, effectively realize accurate identification of largescale parameters. In this paper, the adaptive weighted particle swarm optimization （AWPSO） algorithm is used to identify the C-P spectral model parameters based on typical ground motion records. The results show that the recognition accuracy of the AWPSO algorithm is improved by at least .% compared with the OLS algorithm,,the computational efficiency has been greatly im? proved. ground motion records are selected from the ground motion record database, grouped according to the site classification standards in the building seismic design code. The AWPSO algorithm is used to identify, count the parameters of the C-P spectrum model of various sites. Using K-S test, A-D test, AIC information criterion, the optimal probability distribution model of each parameter is determined,,the correlation coefficient between each parameter is further calculated,,the joint probability density function of C-P spectral model is established. Using the Latin hypercube sampling method, the statistical sampling CP spectral model of the site is obtained,,the power spectrum of the standard transformation is compared, analyzed. The artificial ground motion synthesis method with iterative correction of the power spectrum is used to generate the artificial seismic record with the site characteristics., The Clough-Penzien power spectrum of ground motion （C?P spectrum） has clear physical significance, but needs to identify many parameters. The ordinary least squares （OLS） algorithm has shortcomings such as high requirements for the selection of initial values for nonlinear identification of data,,inability to quickly, effectively realize accurate identification of largescale parameters. In this paper, the adaptive weighted particle swarm optimization （AWPSO） algorithm is used to identify the C-P spectral model parameters based on typical ground motion records. The results show that the recognition accuracy of the AWPSO algorithm is improved by at least .% compared with the OLS algorithm,,the computational efficiency has been greatly im? proved. ground motion records are selected from the ground motion record database, grouped according to the site classification standards in the building seismic design code. The AWPSO algorithm is used to identify, count the parameters of the C-P spectrum model of various sites. Using K-S test, A-D test, AIC information criterion, the optimal probability distribution model of each parameter is determined,,the correlation coefficient between each parameter is further calculated,,the joint probability density function of C-P spectral model is established. Using the Latin hypercube sampling method, the statistical sampling CP spectral model of the site is obtained,,the power spectrum of the standard transformation is compared, analyzed. The artificial ground motion synthesis method with iterative correction of the power spectrum is used to generate the artificial seismic record with the site characteristics. Identification and statistical modeling with applications of Clough‑Penzien power spectrum model parameters[J]. Journal of Vibration Engineering,2023,36(5):1204~1215.]