Description: 粒计算的论文，共11篇，具有很高的参考价值，基于粒计算的文档聚类等等。-Granular computing papers, a total of 11, with a high reference value, document clustering based on granular computing and so on. Platform: |
Size: 2000896 |
Author:hurrican |
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Description: 这是几篇关于粒计算在故障诊断中的应用，对学习粒计算的应用很有帮助。-This is a few on Granular Computing in Fault Diagnosis of learning the application of granular computing helpful. Platform: |
Size: 1180672 |
Author:zhaojie |
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Description: 传统的K-medoids聚类算法的聚类结果随初始中心点的
不同而波动，且计算复杂度较高不适宜处理大规模数据集；
快速K-medoids聚类算法通过选择合适的初始聚类中心改进
了传统K-medoids聚类算法，但是快速K-medoids聚类算法
的初始聚类中心有可能位于同一类簇。为了克服传统的K-
medoids聚类算法和快速K-medoids聚类算法的缺陷，提出
一种基于粒计算的K-medoids聚类算法。-Traditional clustering K-medoids clustering algorithm with the initial centers
Different swings, and a high degree of computational complexity inappropriate handling large data sets
Fast K-medoids clustering algorithm by selecting appropriate initial cluster centers to improve
The traditional K-medoids clustering algorithm, but fast clustering algorithm K-medoids
The initial cluster centers may be located in the same class clusters. In order to overcome the traditional K-
Medoids defect clustering algorithm and fast K-medoids clustering algorithm,
K-medoids one kind of clustering algorithm based on granular computing. Platform: |
Size: 2048 |
Author:问建丽 |
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Description: 传统的K-medoids聚类算法的聚类结果随初始中心点的 不同而波动，且计算复杂度较高不适宜处理大规模数据集； 快速K-medoids聚类算法通过选择合适的初始聚类中心改进 了传统K-medoids聚类算法，但是快速K-medoids聚类算法 的初始聚类中心有可能位于同一类簇。为了克服传统的K- medoids聚类算法和快速K-medoids聚类算法的缺陷，提出 一种基于粒计算的K-medoids聚类算法。(The traditional K-medoids clustering algorithm clustering results with different initial center points and volatility, and high computational complexity is not suitable for processing large data sets; K-medoids clustering algorithm by choosing proper initial cluster centers to improve the traditional K-medoids clustering algorithm, but the initial cluster center of K-medoids clustering algorithm can be located in the same cluster. In order to overcome the shortcomings of the traditional K- medoids clustering algorithm and the fast K-medoids clustering algorithm, a K-medoids clustering algorithm based on granular computing is proposed.) Platform: |
Size: 2048 |
Author:playboyplay2
|
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Description: 在粗糙集与粒计算中，对于常见的几种非线性规划的函数，运用PSO算法求出了相应的决策属性的权重(In rough set and granular computing, PSO algorithm is used to calculate the weights of the corresponding decision attributes for the common functions of nonlinear programming) Platform: |
Size: 6144 |
Author:格式化01 |
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