《计算机应用研究》|Application Research of Computers

全局引导和相互作用的郊狼优化算法及其应用

Coyote optimization algorithm with global guidance and coyote interaction and its application

免费全文下载 (已被下载 次)  
获取PDF全文
作者 张新明,付子豪,陈海燕,刘尚旺,窦智,刘国奇
机构 1.河南师范大学 计算机与信息工程学院,河南 新乡 453007;2.湖北省肿瘤医院 妇瘤科,武汉 430079
统计 摘要被查看 次,已被下载
文章编号 1001-3695(2020)09-030-2711-07
DOI 10.19734/j.issn.1001-3695.2019.04.0136
摘要 针对新型的郊狼优化算法(COA)在解决复杂优化问题时收敛速度慢、全局搜索能力不足的问题,提出了一种嵌入全局引导和相互作用的郊狼优化算法(GCCOA)。首先在组内所有郊狼的成长过程中,构建一种全局引导的alpha狼,增强开采能力,提高收敛速度;然后提出一种相互作用的文化趋势,使得组内的文化趋势受到组内郊狼相互作用的影响,以此提高算法全局搜索能力;最后,将GCCOA运用到CEC2017复杂函数优化和医学图像增强上。大量实验结果表明,与COA、HFPSO、CSPSO和β-GWO等算法相比,在29个函数上,GCCOA获得22个第一,有更好的全局搜索能力和收敛质量。应用于医学图像增强的实验结果表明,与COA等算法相比,GCCOA能更好地解决医学图像增强中参数优化问题。所以,GCCOA是一种很有潜力的优化算法。
关键词 智能优化算法; 郊狼优化算法; 全局引导; 图像增强; 医学图像
基金项目 国家自然科学基金资助项目(U1704158)
河南省高等学校重点科研项目(19A520026)
本文URL http://www.arocmag.com/article/01-2020-09-030.html
英文标题 Coyote optimization algorithm with global guidance and coyote interaction and its application
作者英文名 Zhang Xinming, Fu Zihao, Chen Haiyan, Liu Shangwang, Dou Zhi, Liu Guoqi
机构英文名 1.College of Computer & Information Engineering,Henan Normal University,Xinxiang Henan 453007,China;2.Dept. of Gynecological Tumor,Hubei Cancer Hospital,Wuhan 430079,China
英文摘要 Aiming at the problem, such as novel COA has slow convergence and insufficient global search ability when solving complex optimization problems, this paper proposed an algorithm called GCCOA. Firstly, during the growth of the coyotes in packs, it embedded a global-best guidance coyote to make the exploitation more powerful and to improve the convergence qua-lity of COA. Then, it adopted a cultural tendency with coyote interaction, which was impacted by the interaction of the coyotes in the pack, to improve the global search ability of COA. Finally, it applied GCCOA to complex function optimization and image enhancement. A lot of experimental results on 29 complex functions from CEC2017 set show that GCCOA obtains 22 times of the first place and has better optimization ability than COA, HFSPO, CSPSO and β-GWO. In additional, the experimental results on medical image enhancement show that GCCOA can solve the optimization problem better than comparison algorithms such as COA and so on. So GCCOA is an optimization algorithm.
英文关键词 intelligent optimization algorithm; COA; global-best guidance; image enhancement; medical image
参考文献 查看稿件参考文献
 
收稿日期 2019/4/5
修回日期 2019/5/12
页码 2711-2717
中图分类号 TP181
文献标志码 A