Abstract
Bézier curve is a parametric polynomial that is applied to produce good piecewise interpolation methods with more advantage over the other piecewise polynomials. It is, therefore, crucial to construct Bézier curves that are smooth and able to increase the accuracy of the solutions. Most of the known strategies for determining internal control points for piecewise Bezier curves achieve only partial smoothness, satisfying the first order of continuity. Some solutions allow you to construct interpolation polynomials with smoothness in width along the approximating curve. However, they are still unable to handle the locations of the inner control points. The partial smoothness and non-controlling locations of inner control points may affect the accuracy of the approximate curve of the dataset. In order to improve the smoothness and accuracy of the previous strategies, а new piecewise cubic Bézier polynomial with second-order of continuity C2 is proposed in this study to estimate missing values. The proposed method employs geometric construction to find the inner control points for each adjacent subinterval of the given dataset. Not only the proposed method preserves stability and smoothness, the error analysis of numerical results also indicates that the resultant interpolating polynomial is more accurate than the ones produced by the existing methods.
Highlights
The Missing values of dataset are the common issues in many areas of sciences such as statistics, computer sciences, and geophysics [1,2,3]
The obtained results were compared with the Natural Cubic Spline (Spline) [27], Cubic Hermit Interpolating Polynomial (Pchip) [28], Modified Akima Piecewise Cubic Hermit Interpolation [29], Rational Cubic Ball Interpolation (Ball) [19], and Cubic Natural Curve (Pollock) [15], in terms of errors
The results show that C2 Geometric Bézier Polynomial (C2GBP) excels in non-oscillating curve output since the inner control points are geometrically constructed
Summary
The Missing values of dataset are the common issues in many areas of sciences such as statistics, computer sciences, and geophysics [1,2,3]. By taking the advantages of Bézier curve, researchers started to construct a piecewise cubic Bézier curve at every subinterval of data points in order to improve the smoothness of the interpolating polynomial and increase the accuracy. A geometric structure of piecewise parametric interpolating polynomial employing cubic Bézier curves is proposed for locating the inner control points.
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