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Approximate Multi-Degree Reduction of SG-Bézier Curves Using the Grey Wolf Optimizer Algorithm

机译:使用灰狼优化算法对SG-Bézier曲线进行近似多度约简

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SG-Bézier curves have become a useful tool for shape design and geometric representation in computer aided design (CAD), owed to their good geometric properties, e.g., symmetry and convex hull property. Aiming at the problem of approximate degree reduction of SG-Bézier curves, a method is proposed to reduce the n -th SG-Bézier curves to m- th ( m n ) SG-Bézier curves. Starting from the idea of grey wolf optimizer (GWO) and combining the geometric properties of SG-Bézier curves, this method converts the problem of multi-degree reduction of SG-Bézier curves into solving an optimization problem. By choosing the fitness function, the approximate multi-degree reduction of SG-Bézier curves with adjustable shape parameters is realized under unrestricted and corner interpolation constraints. At the same time, some concrete examples of degree reduction and its errors are given. The results show that this method not only achieves good degree reduction effect, but is also easy to implement and has high accuracy.
机译:由于SG-Bézier曲线具有良好的几何特性,例如对称性和凸包特性,因此已成为计算机辅助设计(CAD)中用于形状设计和几何表示的有用工具。针对SG-Bézier曲线的近似降阶问题,提出了一种将第n条SG-Bézier曲线简化为第m-(m

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