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

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  • 1College of Mathematics and Computer Application, Shangluo University, Shangluo 726000, China.

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Summary

This study introduces a new method for merging disk Wang-Ball (DWB) curves using the Bi-directional Evolutionary Snake Optimizer (BEESO). BEESO effectively reduces merging errors, aiding in product shape data compression and transfer.

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approximate mergerdisk Wang–Ball curveserror minimizationmodified snake optimizer

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Area of Science:

  • Computer-Aided Geometric Design (CAGD)
  • Computational Geometry
  • Optimization Algorithms

Background:

  • Merging curves is crucial for simplifying complex shapes in CAGD.
  • Traditional methods struggle with merging Disk Wang-Ball (DWB) curves due to their complexity.
  • Efficient data compression and transfer of product shapes remain a challenge.

Purpose of the Study:

  • To propose an effective method for the approximate merging of DWB curves.
  • To address the difficulties encountered in merging DWB curves.
  • To establish an optimization model for minimizing merging errors.

Main Methods:

  • Developed an approximate merging model for DWB curves, treating it as an optimization problem.
  • Introduced the Bi-directional Evolutionary Snake Optimizer (BEESO) for enhanced convergence.
  • BEESO integrates snake optimizer (SO) with bi-directional search, evolutionary population dynamics, and elite opposition-based learning.

Main Results:

  • BEESO demonstrated effectiveness in solving the approximate merging model.
  • Numerical examples validated the method's ability to minimize merging errors.
  • The proposed approach offers a novel solution for DWB curve merging.

Conclusions:

  • The BEESO-based method provides an efficient solution for approximate DWB curve merging.
  • This technique facilitates improved compression and transfer of product shape data in CAGD.
  • The study offers a new computational approach for geometric data manipulation.