K-means Hybrid Iterative Clustering Based on Memory Transfer Sailfish Optimization

K-means Hybrid Iterative Clustering Based on Memory Transfer Sailfish Optimization

Aimed at the problem that the existing K-means clustering (KMC) algorithm is greatly affected by initialization, and the randomly generated clustering center can easily make the clustering result fall into local optimum and stop iterating, resulting in low clustering accuracy and poor robustness, a...

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Bibliographic Details
Main Author: HUANG He, XIONG Wu, WU Kun, WANG Huifeng, RU Feng, WANG Jun
Format: Article
Language:zho
Published: Editorial Office of Journal of Shanghai Jiao Tong University 2022-12-01
Series:Shanghai Jiaotong Daxue xuebao
Subjects:
sailfish algorithm
adaptive memory transfer correction strategy
<i>k</i>-means clustering (kmc)
maximum and minimum distance product
uci standard data set
Online Access:https://xuebao.sjtu.edu.cn/article/2022/1006-2467/1006-2467-56-12-1638.shtml

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https://xuebao.sjtu.edu.cn/article/2022/1006-2467/1006-2467-56-12-1638.shtml

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