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An automatic clustering algorithm inspired by membrane computing

机译:受膜计算启发的自动聚类算法

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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. (C) 2015 Elsevier B.V. All rights reserved.
机译:膜计算是一类分布式并行计算模型。从膜计算的结构和内在机理的启发出发,提出了一种膜聚类算法来解决自动聚类问题,该算法以全连接结构的组织样膜系统为计算框架。此外,基于其特殊的结构和内在机理,开发了一种改进的速度位置模型作为演化规则。在进化通讯机制的控制下,类组织膜系统不仅能够找到最合适的簇数,而且还能为数据集确定良好的簇划分。六个基准数据集用于评估提出的膜聚类算法。实验结果表明,该算法优于最近文献报道的三种最新的自动聚类算法。 (C)2015 Elsevier B.V.保留所有权利。

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