计算机工程与应用2025，Vol.61Issue(4)：99-113,15.DOI:10.3778/j.issn.1002-8331.2405-0018
融合组织P系统的自适应t分布蜣螂算法
Fusion of Adaptive t-Distribution Dung Beetle Optimizer Algorithm with Tissue P System
摘要
Abstract
In response to the problem that the original dung beetle optimizer algorithm(DBO)is susceptible to its own influence,resulting in an imbalance between local and global search,and easily falling into the local optima.This paper proposes an adaptive t-distribution DBO with tissue-like membrane(MC-TDBO).Design adaptive inertia factors to change the step sizes of breeding dung beetles and stealing dung beetles,dynamically adjust the exploration range of indi-vidual dung beetles,and coordinate and optimize the global search and local development capabilities of the algorithm.Introduce whale optimization algorithm to improve the foraging behavior,promote the population to move closer to the opti-mal position,and enhance the computational accuracy of the algorithm.Combine success rate with adaptive t-distribution to enhance the ability to escape local optima.Combine tissue-like P system in membrane computing with improved DBO algorithm to enhance algorithm convergence efficiency.Simulated test using 14 benchmark functions shows that com-pared to the original DBO algorithm,MC-TDBO algorithm and other four algorithms have significantly improved optimi-zation speed,solution accuracy,and stability.Finally,MC-TDBO is used in threshold segmentation for the further valida-tion of its effectiveness.关键词
组织P系统/蜣螂算法/自适应t分布/动态惯性权重Key words
tissue-like P system/dung beetle optimizer algorithm/adaptive t-distribution/dynamic inertia weight分类
信息技术与安全科学引用本文复制引用
许家昌,江琳,苏树智..融合组织P系统的自适应t分布蜣螂算法[J].计算机工程与应用,2025,61(4):99-113,15.基金项目
安徽理工大学医学专项培育项目(YZ2023H2B008,YZ2023H2A007) （YZ2023H2B008,YZ2023H2A007）
南方林业与生态应用技术国家工程实验室开放基金项目(2023NFLY08) （2023NFLY08）
国家自然科学基金面上项目(52374155) （52374155）
安徽省自然科学基金面上项目(2308085MF218) （2308085MF218）
安徽省高等学校自然科学研究基金重大项目(2022AH040113). （2022AH040113）
