具有非均匀变异的多策略麻雀搜索算法

IF 3.2 Q2 AUTOMATION & CONTROL SYSTEMS
Zuwei Huang, Donglin Zhu, Yujia Liu, Xiao Wang
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引用次数: 2

摘要

麻雀搜索算法(SSA)存在陷入局部最优的倾向,以及对零位置的偏好。为此,我们提出了一种非均匀变异麻雀搜索算法(NMSSA)。在种群初始化阶段,我们引入了帐篷混沌映射和基于广义对立的学习策略来提高种群的多样性;引入自适应权值,动态调整发现器的搜索范围,提高算法的搜索效率;为了防止算法在早期偏离目标,我们采用非均匀突变策略来提高从者搜索的灵活性,从而提高算法的收敛精度。最后,采用翻筋斗策略降低算法陷入局部最优的概率。在10个基准函数和CEC2017函数的测试实验中,我们将NMSSA的实验结果与其他算法的实验结果进行了比较,实验结果验证了NMSSA的有效性。此外,我们还将NMSSA应用于工程问题优化和K-means图像分割,实验结果表明NMSSA在实际应用中具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-strategy sparrow search algorithm with non-uniform mutation
Sparrow search algorithm (SSA) suffers from a tendency to fall into local optima, as well as a preference for zero locations. Therefore, to improve this drawback, we propose a non-uniform mutation sparrow search algorithm (NMSSA). In the initialization stage of the population, we introduce a tent chaos map and a generalized opposition-based learning strategy to improve the diversity of the population; We introduce adaptive weight to dynamically adjust the search range of the discoverer to improve the search efficiency of the algorithm; To prevent the algorithm from deviating from the target in the early stage, we adopt a non-uniform mutation strategy to improve the flexibility of the follower search to improve the convergence accuracy of the algorithm. Finally, we use the somersault strategy to reduce the probability of the algorithm falling into local optimum. In the test experiments with 10 benchmark functions and CEC2017 functions, we compare the experimental results of NMSSA with those of other algorithms, and the experimental results verify the effectiveness of NMSSA. In addition, we also applied NMSSA to engineering problems optimization and K-means image segmentation, and the experimental results show that NMSSA has good performance in practical applications.
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来源期刊
Systems Science & Control Engineering
Systems Science & Control Engineering AUTOMATION & CONTROL SYSTEMS-
CiteScore
9.50
自引率
2.40%
发文量
70
审稿时长
29 weeks
期刊介绍: Systems Science & Control Engineering is a world-leading fully open access journal covering all areas of theoretical and applied systems science and control engineering. The journal encourages the submission of original articles, reviews and short communications in areas including, but not limited to: · artificial intelligence · complex systems · complex networks · control theory · control applications · cybernetics · dynamical systems theory · operations research · systems biology · systems dynamics · systems ecology · systems engineering · systems psychology · systems theory
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