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Application of K-means Algorithm Based on Ant Clustering Algorithm in Macroscopic Planning of Highway Transportation Hub

机译:K均值算法在蚂蚁聚类算法在公路运输中心宏观规划中的应用

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Development of highway transportation promotes sustainable and rapid development in economy of our country effectively. But construction of highway and transportation hub shows the nature of unbalance. So highway main hub cities must be clustered using cluster analysis, and then divided level in order to functional analyze. K-means algorithm is the most widely used algorithm in clustering analysis, which clustering numbers and initial clustering centers are uncertain. This paper proposes application of K-means algorithm in macroscopic planning of highway transportation hub based on ant clustering algorithm. The experimental results show this algorithm can more effectively solved clustering problem than K-means algorithm and ant clustering algorithm.
机译:高速公路运输的发展促进了我国经济的可持续发展和快速发展。但公路和交通中心的建设显示了不平衡的性质。因此,高速公路主要中心城市必须使用集群分析进行聚类,然后分割级别以便功能分析。 K-means算法是群集分析中最广泛使用的算法,其中聚类数字和初始聚类中心是不确定的。本文提出了基于蚂蚁聚类算法的公路运输集线器宏观规划的K-ic算法。实验结果表明该算法可以更有效地解决了比K-Means算法和蚂蚁聚类算法的聚类问题。

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