基 于 密 度 峰 值 的 海 量 云 数 据 模 糊 聚 类 算 法 设 计

Xi Guang Zhang, Long Fei Zhang, Yu Xi Ma, Yin Ting Fan

科研成果: 期刊稿件文章同行评审

摘要

In order to cluster massive cloud data accurately,a fuzzy clustering algorithm for massive cloud data based on peak density is proposed. The cloud data with noise is separated by BP neural network,and the output noise is reconstructed by singular value decomposition to obtain the noise output by the joint algorithm. The cloud data with noise is subtracted from the output noise to obtain the cloud data after noise removal. The density peak is combined with the optimized fuzzy clustering algorithm to adaptively form the initial clustering center,determine the number of clusters,and finally realize the fuzzy clustering of massive cloud data. Experimental results show that the clustering effect and efficiency of the proposed algorithm are significantly better than other algorithms.

投稿的翻译标题Design of fuzzy clustering algorithm for massive cloud data based on density peak
源语言繁体中文
页(从-至)1401-1406
页数6
期刊Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)
54
5
DOI
出版状态已出版 - 5月 2024

关键词

  • bat algorithm
  • fuzzy clustering
  • massive cloud data
  • neural network
  • peak density
  • singular value

指纹

探究 '基 于 密 度 峰 值 的 海 量 云 数 据 模 糊 聚 类 算 法 设 计' 的科研主题。它们共同构成独一无二的指纹。

引用此