To improve the precisions of pose error analysis for 6-dof parallel kinematic mechanism( PKM)during assembly quality control,a Sobol sequence based on Quasi Monte Carlo( QMC) method is introduced and implemented in po...To improve the precisions of pose error analysis for 6-dof parallel kinematic mechanism( PKM)during assembly quality control,a Sobol sequence based on Quasi Monte Carlo( QMC) method is introduced and implemented in pose accuracy analysis for the PKM in this paper. The Sobol sequence based on Quasi Monte Carlo with the regularity and uniformity of samples in high dimensions,can prevail traditional Monte Carlo method with up to 98. 59% and 98. 25% enhancement for computational precision of pose error statistics.Then a PKM tolerance design system integrating this method is developed and with it pose error distributions of the PKM within a prescribed workspace are finally obtained and analyzed.展开更多
针对障碍期权的定价问题,给出了一种高效的蒙特卡罗(Monte Carlo,MC)模拟方法——基于布朗桥构造路径的随机化拟蒙特卡罗(Brownian bridge path randomization quasi Monte Carlo,BBPR-QMC)方法.首先,用Faure序列代替MC方法中的随机序列...针对障碍期权的定价问题,给出了一种高效的蒙特卡罗(Monte Carlo,MC)模拟方法——基于布朗桥构造路径的随机化拟蒙特卡罗(Brownian bridge path randomization quasi Monte Carlo,BBPR-QMC)方法.首先,用Faure序列代替MC方法中的随机序列,得到了Faure序列的拟蒙特卡罗(quasi Monte Carlo,QMC)模拟方法;其次,应用Moro算法得到了随机化拟蒙特卡罗(randomization quasi Monte Carlo,R-QMC)模拟方法;最后,将QMC方法和R-QMC方法结合,利用布朗桥技术来降低有效维,得到障碍期权定价的BBPR-QMC方法.数值试验表明,与MC方法和R-QMC方法相比较,BBPR-QMC方法模拟的价格与真实价格更接近、收敛速度更快.数值试验证实,BBPR-QMC方法是一种高效求解障碍期权定价的数值方法.展开更多
基金Sponsored by the National Defense Basic Scientific Research Program(Grant No.A0320110019)the Shanghai Science and Technology Innovation Action Plan(Grant No.11DZ1120800)
文摘To improve the precisions of pose error analysis for 6-dof parallel kinematic mechanism( PKM)during assembly quality control,a Sobol sequence based on Quasi Monte Carlo( QMC) method is introduced and implemented in pose accuracy analysis for the PKM in this paper. The Sobol sequence based on Quasi Monte Carlo with the regularity and uniformity of samples in high dimensions,can prevail traditional Monte Carlo method with up to 98. 59% and 98. 25% enhancement for computational precision of pose error statistics.Then a PKM tolerance design system integrating this method is developed and with it pose error distributions of the PKM within a prescribed workspace are finally obtained and analyzed.
文摘针对障碍期权的定价问题,给出了一种高效的蒙特卡罗(Monte Carlo,MC)模拟方法——基于布朗桥构造路径的随机化拟蒙特卡罗(Brownian bridge path randomization quasi Monte Carlo,BBPR-QMC)方法.首先,用Faure序列代替MC方法中的随机序列,得到了Faure序列的拟蒙特卡罗(quasi Monte Carlo,QMC)模拟方法;其次,应用Moro算法得到了随机化拟蒙特卡罗(randomization quasi Monte Carlo,R-QMC)模拟方法;最后,将QMC方法和R-QMC方法结合,利用布朗桥技术来降低有效维,得到障碍期权定价的BBPR-QMC方法.数值试验表明,与MC方法和R-QMC方法相比较,BBPR-QMC方法模拟的价格与真实价格更接近、收敛速度更快.数值试验证实,BBPR-QMC方法是一种高效求解障碍期权定价的数值方法.
