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An improved black widow optimization algorithm for surfaces conversion
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AI
DOI：10.1007/s10489-022-03715-w.png)
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Abstract
En 中文
Bezier surfaces and Q-Bezier surfaces are effective modeling tools for shape design in computer-aided geometric design, computer vision, and computer graphics. The mutual conversion between these two kinds of surfaces is a pivotal and knotty technique in CAD/CAM. In this paper, the conversion between Q-Bezier surfaces and rectangular Bezier surfaces is investigated. However, due to the uncertain parameters of the Q-Bezier surfaces, the approximation conversion from rectangular Bezier surfaces to Q-Bezier surfaces can be regarded as an optimization problem, which is effectively dealt with by swarm intelligence algorithm. In this regard, an enhanced Black Widow Optimization called LDBWO is proposed to find more suitable shape parameters to obtain optimal approximation Q-Bezier surfaces, which are closer to the given Bezier surfaces. The LDBWO algorithm overcomes the shortcomings of standard BWO algorithm such as low accuracy, slow convergence, and is easy to fall into local optimum by introducing golden sine learning strategy and diffusion process. Furthermore, to confirm and validate the performance of the LDBWO, eight well-known intelligent algorithms are compared with the LDBWO on various benchmark functions and engineering examples. Finally, by minimizing the conversion error defined by the L-2-norm, the optimization model of the approximation conversion from rectangular Bezier surfaces to Q-Bezier surfaces is established. Several representative numerical examples are provided to illustrate the accuracy and efficiency of the proposed methods.
Keywords:
Black widow optimization algorithm
Q-Bezier surfaces
Rectangular Bezier surfaces
Shape parameters
Surface conversion
Journal
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3.5
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7.5K
Citations:
1.7W
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