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Updated: May 17, 2026

Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray
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线性阵列天线的设计与不平等的间距基于改进的花优化算法.

Jianhui Li1, Yan Liu1, Wanru Zhao1

  • 1School of Physics and Electronic Information, Yunnan Normal University, Kunming 650500, China.

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概括

一个新的混乱交换非线性子优化 (CENDO) 算法通过减少侧叶水平和创建深度零值来改进天线阵列模式. 这种增强的方法在复杂的电磁环境中优于现有的算法.

关键词:
这就是CENDO算法.后勤帐混乱的地图绘制.非线性控制因子的非线性控制因子不均距离的线性数组的合成.

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科学领域:

  • 电磁主义 电磁主义
  • 天线理论天线理论
  • 优化算法 优化算法

背景情况:

  • 复杂的电磁环境需要先进的雷达系统.
  • 阵列天线对于增强雷达对干扰和检测的能力至关重要.
  • 现有的优化算法在天线模式优化方面与精度和收作斗争.

研究的目的:

  • 介绍混沌交换非线性花优化 (CENDO) 算法,用于优化非等距离的天线阵列模式.
  • 通过最大限度地降低侧叶水平 (SLL) 和实现深度零值来提高天线性能.
  • 评估CENDO算法的有效性与其他领先的优化技术相比.

主要方法:

  • 开发了CENDO算法,这是花优化 (DO) 算法的改进版本.
  • 模拟了五个实验示例,以测试CENDO在优化非等距离天线阵列方面的性能.
  • 对CENDO与DO,PSO,WOA,GOA,SSA等算法进行比较分析.

主要成果:

  • 在三个模拟示例中,CENDO在优化非等距离数组时实现了最低的SLL.
  • 在另外两个例子中,CENDO在同时减少SLL和实现深度零值方面表现出卓越的表现.
  • 该算法在五次实验模拟中始终超过了所有比较方法.

结论:

  • 对于非等距离的天线阵列模式,CENDO算法提供了卓越的优化能力.
  • CENDO有效地降低了侧叶水平并加深了零值,这对雷达系统性能至关重要.
  • 这种算法是解决复杂电磁问题的强有力的候选者.