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A Combination of Mixture Genetic Algorithm And Fuzzy C-means Clustering Algorithm

机译:混合遗传算法与模糊C均值聚类算法的组合

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Firstly, the paper makes a briefly analysis and comment about the Fuzzy C-means Clustering Algorithm. Then a new kind of Hybrid Genetic Algorithm is proposed on the base of the combination of Genetic Algorithm and Simulated Annealing Algorithm, and it is applied in Fuzzy C-means Clustering. It overcomes the locality and the Sensitivity to initial clustering central of Fuzzy C-means Clustering, by using randomness and parallelism in Hybrid Genetic Algorithm searching. And a new Tree-shaped coding scheme adapted to fuzzy clustering is adopted in the Genetic Algorithm. In the end, the paper supplies the detailed design of the method. Simulation experiments show the relatively high efficiency and recognition accuracy of the method, which has extensive application prospect in many fields, such as Pattern Recognition, Data Mining, and so on.
机译:首先,对模糊C-均值聚类算法进行简要的分析和评述。然后在遗传算法与模拟退火算法相结合的基础上,提出了一种新的混合遗传算法,并将其应用于模糊C均值聚类。通过在混合遗传算法搜索中使用随机性和并行性,克服了模糊C均值聚类对初始聚类中心的局部性和敏感性。遗传算法采用了一种新的适合模糊聚类的树形编码方案。最后,本文提供了该方法的详细设计。仿真实验表明,该方法具有较高的效率和识别精度,在模式识别,数据挖掘等许多领域具有广阔的应用前景。

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