社会共同进化和Sine混乱的反对学习 黑猩猩优化特征选择算法
Li Zhang1,2, XiaoBo Chen3,4
1College of Computer Engineering, Jiangsu University of Technology, Changzhou, 213001, People's Republic of China. zhangli@jstu.edu.cn.
Scientific reports
|July 4, 2024
概括
一个新的算法,社会共同进化和Sine混乱的反对学习黑猩猩优化算法 (SOSCHoA),通过增强群体智能来改善特征选择. 它在机器学习任务中实现了更好的准确性和稳定性.
科学领域:
- 机器学习 机器学习
- 群集情报 群集情报 群集情报
- 优化算法 优化算法
背景情况:
- 功能选择在机器学习中至关重要,集群智能算法提供强大的优化能力.
- 黑猩猩优化算法 (CHoA) 以其速度和简单性而闻名,但难以平衡勘探和开发,导致过早的融合.
- 这些局限性阻碍了CHoA在复杂的特征选择场景中的有效性.
研究的目的:
- 为了解决标准的黑猩猩优化算法 (CHoA) 在特征选择中的局限性.
- 引入一个增强的算法,社会共进和Sine混乱的反对学习黑猩猩优化算法 (SOSCHoA),以提高优化准确度和防止过早的融合.
- 评估SOSCHoA在高维分类数据集上的性能.
主要方法:
- 拟议的社会共同进化和Sine混沌对立学习黑猩猩优化算法 (SOSCHoA) 整合了社会共同进化,以改善本地搜索.
- 纳入Sine混沌对立学习以增强人口多样性并减轻局部最佳陷.
- 该算法的有效性通过对12个高维分类数据集进行广泛的实验来测试.
主要成果:
- 与现有算法相比,SOSCHoA在多个指标上表现出优异的性能.
- 改进的算法在测试数据集上实现了更高的分类准确性.
- 在特征选择任务中,SOSCHoA表现出更好的融合速度和更高的稳定性.
结论:
- 社会共同进化和Sine混沌对立学习黑猩猩优化算法 (SOSCHoA) 有效地解决了标准CHoA对特征选择的局限性.
- 在分类准确性,收性和稳定性方面,SOSCHoA提供了显著的优势,特别是对于高维数据集.
- 未来的研究可以专注于进一步优化SOSCHoA以减少特征维度.
相关概念视频
Frequency-dependent Selection
22.0K
When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
22.0K
Evolutionary Psychology
260
Evolutionary psychology explores the origins of human behavior and mental processes by framing them within the context of natural selection, a theory famously propounded by Charles Darwin. This field asserts that many behaviors common across human societies — ranging from instinctive fear reactions to complex social interactions — arose as evolutionary adaptations. These adaptations enhanced the survival and reproductive success of our ancestors, thereby becoming embedded in the...
260
Types of Selection
40.4K
Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
40.4K
Limits to Natural Selection
31.2K
Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
31.2K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility
3.1K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.1K
Convergent Evolution
27.7K
Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.
27.7K


