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Rapid Simulated Annealing Data Clustering Method based on Silhouette Valid Index and Apparatus Therefore

机译:基于轮廓有效指标的快速模拟退火数据聚类方法

摘要

Disclosed are a method and apparatus for fast simulated annealing data clustering to which a silhouette evaluation function is applied. A simulated annealing data clustering method according to an embodiment of the present invention includes calculating a sum of relative distance ratios between all data; selecting an initial solution based on the sum of the calculated relative distance ratios; and performing simulated annealing data clustering based on a silhouette evaluation function using the selected initial solution, wherein the selecting comprises calculating a selection probability of each data using the sum of the calculated relative distance ratios. and selects a preset number of central data by assigning a random probability value to each of the data and checking whether they are included in the calculated selection probability section, reconstructing a cluster based on the selected central data and reconstructing the reconstructed After generating a solution for each cluster, calculating a silhouette evaluation value for each of the generated solutions, a solution with the best silhouette evaluation value may be selected as the initial solution.
机译:本发明公开了一种应用轮廓评估函数的快速模拟退火数据聚类方法和装置。根据本发明实施例的模拟退火数据聚类方法包括计算所有数据之间的相对距离比之和;基于计算出的相对距离比之和选择初始解;以及使用选择的初始解基于轮廓评估函数执行模拟退火数据聚类,其中选择包括使用计算出的相对距离比之和计算每个数据的选择概率。以及通过向每个数据分配随机概率值并检查它们是否包括在计算出的选择概率部分中来选择预设数量的中心数据,基于所选择的中心数据重建簇,并在为每个簇生成解之后重建重建的簇,计算每个生成的解决方案的轮廓评估值,可以选择具有最佳轮廓评估值的解决方案作为初始解决方案。

著录项

  • 公开/公告号KR102372252B1

    专利类型

  • 公开/公告日2022-03-08

    原文格式PDF

  • 申请/专利权人

    申请/专利号KR1020200058190

  • 发明设计人 김성수;백준영;

    申请日2020-05-15

  • 分类号G06F16/906;G06F16/28;G06F16/35;G06F17/16;

  • 国家 KR

  • 入库时间 2022-08-25 00:05:16

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