用改进的树种算法优化Butterworth和Bessel波器参数
Mehmet Beşkirli1, Mustafa Servet Kiran2
1Department of Computer Engineering, Karamanoğlu Mehmetbey University, 70200 Karaman, Türkiye.
Biomimetics (Basel, Switzerland)
|November 24, 2023
概括
这项研究使用改进的树种算法 (I-TSA) 优化了活跃波器参数. I-TSA方法证明了过器设计的成功应用和预测,比基本的树种算法提高了性能.
科学领域:
- 电气工程 电气工程
- 信号处理 信号处理
- 计算智能是一种计算智能.
背景情况:
- 主动过器是信号处理的关键电路,比被动过器提供增益和阻抗优势.
- 优化活性波器的参数,特别是电阻和电容器,对于最大限度地提高其功能至关重要.
- 现有的优化算法可能需要对复杂的过器设计任务进行增强.
研究的目的:
- 为了优化第十阶Butterworth和贝塞尔活性波器的参数.
- 通过结合基于对立的学习 (OBL) 来引入改进的树种子算法 (I-TSA).
- 评估I-TSA与基本树种子算法 (TSA) 和用于过器设计的其他算法的性能.
主要方法:
- 利用树种子算法 (TSA),一种以自然为灵感的优化技术.
- 集成基于对立的学习 (OBL) 与TSA创建一个增强版本 (I-TSA).
- 应用I-TSA来优化第十阶Butterworth和Bessel波器拓的参数.
主要成果:
- I-TSA方法成功优化了活跃波器参数,证明了它对设计问题的适用性.
- 实验结果证实了I-TSA在执行准确的过器预测方面的有效性.
- 与基本的TSA和其他测试算法相比,I-TSA显示了更好的性能.
结论:
- 拟议的I-TSA是优化活跃波器参数的可行和有效方法.
- 这种方法提供了一个强大的解决方案,以提高活性过器的性能和功能.
- 该研究强调了混合优化算法在先进的电气工程应用中的潜力.
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