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泥模具算法的进步:一个全面的调查
Yuanfei Wei1,2, Zalinda Othman1, Kauthar Mohd Daud1
1Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.
Biomimetics (Basel, Switzerland)
|January 22, 2024
概括
这篇评论详细介绍了粘液模具算法 (SMA),这是一个群集智能技术. 它涵盖了SMA理论,变体和优化和机器学习中的应用,并建议未来的研究方向.
科学领域:
- 计算智能是一种计算智能.
- 群集情报 群集情报 群集情报
- 优化算法 优化算法
背景情况:
- 粘液模具算法 (SMA) 是一种以自然为灵感的元启发.
- 它模仿了粘液菌的食行为.
- 由于其有效性,SMA已经获得了大量的研究兴趣.
研究的目的:
- 提供关于粘液模具算法 (SMA) 的全面审查.
- 总结SMA最近的进展和应用.
- 确定SMA的未来研究机会.
主要方法:
- 系统的文献审查来自谷歌学者 (130篇文章) (2022-2023年).
- 描述SMA核心理论的描述.
- 基于改善策略的SMA变体的分类.
主要成果:
- 详细解释SMA的理论基础.
- 各种改进的SMA变体的分类.
- 概述SMA的应用领域,包括工程,能源,机器学习,网络,调度和图像细分.
结论:
- 粘液模具算法是各种优化和人工智能任务中宝贵的工具.
- 建议对SMA的多目标,离散和神经网络应用进行进一步的研究.
- 审查强调了SMA在继续发展和更广泛应用方面的潜力.
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