区间Bezier曲线的模糊规则逼近

Erkan Ülker, A. Arslan
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引用次数: 0

摘要

通常,我们对结点和控制点作为变量感兴趣,以便从许多测量数据点中找到良好的贝塞尔模型。在本文中,我们根据曲线的曲率和弯曲等几何信息,从给定的分布数据点中选择好的结点。根据模糊规则基选取的结点,将控制点估计为一个区间,建立了区间贝塞尔曲线。我们用最小二乘误差比较了这些曲线和分布数据。为了获得最合适的区间控制点宽度,我们向用户介绍了区间Bezier曲线,它对变化的误差容忍度最小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The approximation of interval Bezier curves by a fuzzy rule-based system
Generally, we are interested in knots and control points as variables for finding a well Bezier model from many measuring data points. In this paper, we have selected good knots from given distributed data points on the basis of geometrical information such as curvature and bending of the curve. We have developed interval Bezier curves by estimating control points as an interval according to the knots which are selected by fuzzy rule basis. We have compared these curves and distributed data with the least squares error. We introduced, to the user the as interval Bezier curve, the one who has the minimum error toleration with variations in order to obtain most appropriate widths of Interval control points.
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