基于刺激-响应机制的改进鸡群算法
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郑州轻工业大学

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TP18

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国家自然科学基金河南联合基金;国家自然科学基金青年基金;中原千人计划;食管癌防治国家重点实验室开放基金


Chicken swarm optimization algorithm based on stimulus-response mechanism
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Zhengzhou University of Light Industry

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    摘要:

    针对鸡群算法收敛速度慢且容易陷入局部最优的不足,从平衡勘探与开发的角度提出一种基于刺激-响应机制的改进鸡群算法。首先,考虑公鸡的引领作用为其设计勘探和开发两种搜索方程。其次,根据种群聚集度和平均改进度定义执行搜索方程的刺激和阈值。最后,在刺激-响应机制下,公鸡充分发挥引领作用,带领鸡群完成勘探与开发。将改进算法用于基准函数优化和食管癌生存风险预测模型优化,并与其他改进的鸡群算法、粒子群算法和人工蜂群算法进行对比,结果表明了所提算法的有效性。

    Abstract:

    The original chicken swarm optimization algorithm converges slowly and easily falls into the local optimum. To overcome this issue, this paper proposes a chicken swarm optimization algorithm based on stimulus-response mechanism from the perspective of exploration-exploitation balance. Firstly, two search equations focusing on exploration and exploitation respectively are designed for roosters. Secondly, the stimulus and threshold of performing different search equations are designed according to population aggregation degree and average improvement degree. Finally, roosters play a leading role and guide the chickens to complete the exploration and exploitation under the stimulus-response mechanism. The experimental results on benchmark functions and survival risk prediction of esophageal cancer show the high efficiency of the proposed algorithm, when compared with other improved chicken swarm optimization algorithms, particle swarm optimization algorithms and artificial bee colony algorithms.

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历史
  • 收稿日期:2021-06-18
  • 最后修改日期:2021-09-17
  • 录用日期:2021-09-22
  • 在线发布日期: 2021-10-01
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