| 引用本文： |
-
周甜,麦雄发,刘利斌,郑贵林.融合疯狂秃鹰搜索的混沌正余弦算法[J].广西科学,2025,32(1):106-120. [点击复制]
- ZHOU Tian,MAI Xiongfa,LIU Libin,ZHENG Guilin.A Chaotic Sine Cosine Algorithm Based on Crazy Bald[CDF*3]Eagle
Search[J].Guangxi Sciences,2025,32(1):106-120. [点击复制]
|
|
| 摘要: |
| 针对正余弦算法(Sine Cosine Algorithm,SCA)在解决优化问题时存在收敛速度慢、计算精度低等缺陷,本文提出一种融合疯狂秃鹰搜索算法的混沌正余弦算法(Chaotic Sine Cosine Algorithm based on Crazy Bald-eagle Search,CSCA-CBS)。CSCA-CBS采用结合Logistic与Tent的混合混沌映射进行种群初始化,从而获得更加均匀和多样的初始种群;受秃鹰搜索算法所启发,CSCA-CBS采用带有疯狂算子的秃鹰搜索策略,该策略能够提升CSCA-CBS的全局探索能力;为了在迭代后期避免陷入局部最优区域,CSCA-CBS使用逐维反向柯西变异策略对种群进行有规律的扰动,极大地集成了反向学习和柯西变异的优势。在15个基准函数上进行的仿真实验结果表明,CSCA-CBS在计算代价和可靠性、解的质量分析以及收敛性能等方面优于多种先进的SCA变体和非SCA基准算法。此外,土壤水分特征曲线的参数反演实验进一步验证了CSCA-CBS的实用性和有效性。 |
| 关键词: 正余弦算法 Logistic-Tent混沌映射 秃鹰搜索算法 疯狂算子 参数反演 |
| DOI：10.13656/j.cnki.gxkx.20241106.001 |
| 投稿时间：2024-06-25修订日期：2024-09-09 |
| 基金项目:国家自然科学基金项目(12361087),广西科技计划项目(桂科AD23023003)和广西研究生教育创新计划项目(JGY2024267)资助. |
|
A Chaotic Sine Cosine Algorithm Based on Crazy Bald[CDF*3]Eagle
Search |
|
ZHOU Tian, MAI Xiongfa, LIU Libin, ZHENG Guilin
|
| (Guangxi Applied Mathematics Center, Nanning Normal University, Nanning, Guangxi, 530100, China) |
| Abstract: |
| Aiming at the slow convergence and low computational accuracy of the Sine Cosine Algorithm (SCA) in optimization problems,a Chaotic Sine Cosine Algorithm based on Crazy Bald-eagle Search (CSCA-CBS) is proposed.CSCA-CBS employs Logistic-Tent chaotic mapping for population initialization,thereby obtaining a more uniform and diverse initial population.Inspired by the bald-eagle search algorithm,CSCA-CBS adopts a bald-eagle search strategy with a crazy operator to enhance its global exploration capability.To avoid falling into local optima during later iterations,CSCA-CBS utilizes a dimension-by-dimension reverse Cauchy mutation strategy to systematically perturb the population,effectively integrating the advantages of opposition-based learning and Cauchy mutation.Simulation experiments with 15 benchmark functions show that the CSCA-CBS can outperform state-of-the-art SCA variants and four non-SCA in terms of computational cost and reliability,solution quality analysis,and convergence performance.Additionally,parameter inversion experiments on soil moisture characteristic curves further validate the excellent practicality and effectiveness of CSCA-CBS. |
| Key words: sine cosine algorithm Logistic-Tent chaotic mapping bald-eagle search algorithm crazy operator parameter inversion |
