Ameliorated Snake Optimizer-Based Approximate Merging of Disk Wang–Ball Curves

A method for the approximate merging of disk Wang–Ball (DWB) curves based on the modified snake optimizer (BEESO) is proposed in this paper to address the problem of difficulties in the merging of DWB curves. By extending the approximate merging problem for traditional curves to disk curves and view...

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Bibliographic Details
Main Authors: Jing Lu, Rui Yang, Gang Hu, Abdelazim G. Hussien
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Biomimetics
Subjects:
Online Access:https://www.mdpi.com/2313-7673/9/3/134
Description
Summary:A method for the approximate merging of disk Wang–Ball (DWB) curves based on the modified snake optimizer (BEESO) is proposed in this paper to address the problem of difficulties in the merging of DWB curves. By extending the approximate merging problem for traditional curves to disk curves and viewing it as an optimization problem, an approximate merging model is established to minimize the merging error through an error formulation. Considering the complexity of the model built, a BEESO with better convergence accuracy and convergence speed is introduced, which combines the snake optimizer (SO) and three strategies including bi-directional search, evolutionary population dynamics, and elite opposition-based learning. The merging results and merging errors of numerical examples demonstrate that BEESO is effective in solving approximate merging models, and it provides a new method for the compression and transfer of product shape data in Computer-Aided Geometric Design.
ISSN:2313-7673