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一个分层的多领导层正弦共弦算法来解决全球优化和数据分类:COVID-19案例研究

Mingyang Zhong1, Jiahui Wen2, Jingwei Ma3

  • 1College of Artificial Intelligence, Southwest University, 400715, China.

Computers in biology and medicine
|July 21, 2023
PubMed
概括

层次多领导的正弦共弦算法 (HMLSCA) 通过改善人口多样性和平衡探索来提高优化. 这种新的方法在基准测试,医疗数据分类和COVID-19诊断方面实现了卓越的性能.

关键词:
在 COVID-19 疫情中,数据分类数据的分类.功能权重的权重是特征权重.sinus 和 cosine 的算法支持矢量机器的支持矢量机器.

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