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Updated: Sep 13, 2025

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Operation of the Collaborative Composite Manufacturing CCM System
Published on: October 1, 2019
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用多策略增强的Coati优化算法对Sid-Ball曲线的多度减少和工程设计
Feng Zou1, Xia Wang1, Weilin Zhang1
1School of Science, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Biomimetics (Basel, Switzerland)
|July 25, 2025
概括
这项研究引入了一种新的方法来减少赛德-巴尔曲线的程度,有效地保留几何特征. 一个新的优化算法,MSECOA,在复杂曲线近似的准确性和效率方面表现出卓越的性能.
科学领域:
- 计算机辅助几何设计 (CAGD)
- 计算几何学计算几何学
- 优化算法优化算法
背景情况:
- 赛德球曲线在CAGD中对于3D建模,血管修复和路径规划至关重要,因为它们具有几何灵活性.
- 曲线度减小对于优化计算和存储资源至关重要,同时保持基本的几何性质.
研究的目的:
- 为赛德-巴尔曲线开发一种新的度减小模型,以增强几何特征的保存.
- 引入和评估一个多策略增强的协同优化算法 (MSECOA),以提高优化任务的性能.
主要方法:
- 一个使用欧几里德距离和曲率数据的新度减小模型.
- 开发了多策略增强的coati优化算法 (MSECOA),结合了基于对立的学习,健身距离平衡,动态螺旋搜索和自适应差异演变.
- 使用IEEE CEC2017和CEC2022基准函数和受约束的工程优化问题进行性能评估.
主要成果:
- 与其他九个高度引用的算法相比,MSECOA算法表现出卓越的融合,准确性和稳定性.
- 拟议的度减小模型显著改善了赛德-巴尔曲线中几何特征的保存.
- 该MSECOA算法在工程优化和有效应用中显示出强大的实用实用性,用于Said-Ball曲线的多度减小近似.
结论:
- 新的度减小模型和MSECOA算法为CAGD中复杂的曲线度减小任务提供了高效和准确的解决方案.
- 该研究验证了MSECOA的效率和精度,为几何设计和优化挑战提供了宝贵的工具.
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