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结合磨光法和最优化理论提出一种随机优化磨光算法(SOS算法),算法通过原始值的参数化和调整幅度的修改,利用优化理论优化控制点.实例表明,随机优化磨光算法比样条修正磨光法和灰色马尔可夫链预测模型精度要高得多;而且所得到的误差变化更稳定.
Combining the polishing method and the optimization theory, a stochastic optimization polishing algorithm (SOS algorithm) is proposed, which optimizes the control points through the parameterization and adjustment of the original values and the optimization theory.The examples show that the stochastic optimization algorithm Spline correction and gray Markov chain prediction model prediction accuracy is much higher; and the resulting error is more stable.