基于多变量非高斯随机过程间的相关性,将发展的单变量非高斯过程自回归和自回归滑动平均(AR和ARMA)模型模拟算法扩展至多变量非高斯过程的数值模拟.通过AR和ARMA模型系数考虑多变量非高斯过程间的相关性,建立多变量非高斯过程AR和ARMA模型的模拟算法.多变量非高斯风压的数值模拟表明:AR和ARMA模型算法能有效地模拟低斜度、中斜度和高斜度的多变量非高斯随机过程.%Based on the correlativity of multivariate non-Gaussian random processes,autoregressive (AR) and autoregressive moving average (ARMA) models proposed for simulating a univariate non-Gaussian stochastic process were extended to simulate multivariate non-Gaussian stochastic processes.Through using coefficients of AR and ARMA models to consider the correlativity of multivariate non-Gaussian processes,the simulation algorithm for multivariate non-Gaussian processes was established with AR and ARMA models.The numerical simulations for multivariate non-Gaussian fluctuating wind pressure indicated that the new simulation algorithm with AR and ARMA models can effectively simulate multivariate non-Gaussian random processes with low skewness,middle one,and high one,respectively.
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