一个具有二进制等级结构和树拓的多目标非洲优化算法,用于大数据优化
Bo Liu1, Yongquan Zhou2, Yuanfei Wei3
1College of Artificial Intelligence, Guangxi University for Nationalities, Nanning 530006, China.
Journal of advanced research
|September 23, 2024
概括
一个新的多目标非洲优化算法与二进制层次结构和树拓 (MO_Tree_BHSAVOA) 有效地解决大数据优化问题. 这种先进的算法性能优于现有的方法,证明了它对大数据挑战的潜力.
科学领域:
- 计算智能是一种计算智能.
- 优化算法 优化算法
- 大数据分析大数据分析
背景情况:
- 由于大数据集的规模和复杂性,大数据优化 (Big-Opt) 问题带来了重大挑战.
- 传统的数据处理方法往往不足以有效管理和优化大数据.
研究的目的:
- 介绍一个新的多目标优化算法,多目标非洲优化算法与二进制层次结构和树拓 (MO_Tree_BHSAVOA).
- 为解决大数据优化问题所带来的独特挑战.
主要方法:
- 纳入二元层次结构 (BHS) 以平衡勘探和开采.
- 使用转移密度估计来对人口演变中的选择压力进行估计.
- 采用树拓来增强逃离局部最佳并保留非主导的解决方案.
主要成果:
- MO_Tree_BHSAVOA展示了高度竞争力的性能.
- 使用弗里德曼测试的统计分析证实了MO_Tree_BHSAVOA在其他多目标优化算法上的优势.
- 该算法被评估在基准函数和现实世界的受约束问题上.
结论:
- 拟议的MO_Tree_BHSAVOA对于大数据优化是有效的.
- 该算法显示了解决大数据环境中复杂的优化挑战的巨大潜力.
关键词:
非洲的优化算法 (AVOA)大数据优化大数据优化二元阶层结构二元阶层结构.这是一种元启发式 (metaheuristic) 启发式.非洲的多目标优化算法 (MO_Tree_BHSAVOA)树的拓学树的拓学.更多相关视频
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