An automatic clustering algorithm inspired by membrane computing

An automatic clustering algorithm inspired by membrane computing
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受膜计算启发的自动聚类算法

DOI:
10.1016/j.patrec.2015.08.008
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发表时间:
2015-12
影响因子:
5.1
通讯作者:
Mario J. Pérez-Jiménez
Mario J. Pérez-Jiménez
中科院分区:
计算机科学3区
文献类型:
--
作者:
Hong Peng;Jun Wang;Peng Shi;Agustín Riscos-Núñez;Mario J. Pérez-Jiménez

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膜计算是一类分布式并行计算模型。受膜计算的结构和内在机制的启发,提出了一种膜聚类算法来处理自动聚类问题,该算法设计了一个具有全连接结构的类组织膜系统作为其计算框架。并根据其特殊的结构和内在机理,建立了改进的速度-位置演化规律模型。在进化-通信机制的控制下,类组织膜系统不仅能找到最合适的簇数,还能确定数据集的良好聚类划分。使用六个基准数据集来评估所提出的膜聚类算法。实验结果表明,该算法优于文献中报道的三种最先进的自动聚类算法。
Membrane computing is a class of distributed parallel computing models. Inspired from the structure and inherent mechanism of membrane computing, a membrane clustering algorithm is proposed to deal with automatic clustering problem, in which a tissue-like membrane system with fully connected structure is designed as its computing framework. Moreover, based on its special structure and inherent mechanism, an improved velocity-position model is developed as evolution rules. Under the control of evolution-communication mechanism, the tissue-like membrane system cannot only find the most appropriate number of clusters but else determine a good clustering partitioning for a data set. Six benchmark data sets are used to evaluate the proposed membrane clustering algorithm. Experiment results show that the proposed algorithm is superior or competitive to three state-and-the-art automatic clustering algorithms recently reported in the literature.
DOI: --
发表时间: 1998-04
期刊: --
影响因子: --
作者:
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通讯作者: E. Falkenauer
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