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The global double cubic B-spline surface interpolation based on particle swarm optimization

机译:基于粒子群算法的全局双三次B样条曲面插值

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a novel B-spline surface interpolation algorithm based on particle swarm optimization is proposed to solve surface optimization problem. Two steps of the algorithm are established in present paper: first, control points are calculated by a given cloud of 3D data points. Second, a set of optimal parameters of the data points is obtained by using particle swarm optimization. The results are compared with the sample points to minimize the root square error. Compared to the traditional method with the smallest root square error, the experimental results have shown that particle swarm optimization yields better solution.
机译:提出了一种基于粒子群算法的B样条曲面插值算法,以解决曲面优化问题。本文建立了算法的两个步骤:首先,通过给定的3D数据点云计算控制点。其次,通过使用粒子群算法获得一组数据点的最优参数。将结果与采样点进行比较,以最小化平方根误差。与具有最小均方根误差的传统方法相比,实验结果表明粒子群优化产生了更好的解决方案。

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