改进的k中心点算法在茶叶拼配中的应用

发布时间：2018-07-03 04:48

  本文选题：茶叶拼配 + 空间聚类　； 参考：《中南民族大学学报(自然科学版)》2017年04期

【摘要】：为了提高茶叶拼配效率,节约人工成本,实现茶叶企业效益最大化,探讨了将茶叶拼配问题建模成多维层次空间聚类问题,并通过定义多维概念分层空间中的相似性度量准则,提出了改进的k中心点算法求解最优拼配方案,并引入Dewey编码提高了求解效率.根据真实数据集上的实验表明:同等实验条件下较人工拼配方式而言,文中所提出的茶叶拼配智能化求解方法大大提高了茶叶企业工作效率和经济利益.
[Abstract]:In order to improve the efficiency of tea blending, save the labor cost and maximize the benefit of tea enterprises, the tea blending problem is modeled as a multi-dimensional hierarchical space clustering problem, and the similarity measurement criterion in the multidimensional concept stratified space is defined. An improved k-center point algorithm is proposed to solve the optimal matching scheme, and Dewey coding is introduced to improve the efficiency of the solution. According to the experiments on the real data set, it is shown that the intelligent solution method of tea blending in the same experimental condition greatly improves the efficiency and economic benefit of tea enterprises.
【作者单位】： 中南民族大学计算机科学学院;
【基金】：国家科技支撑计划项目子课题(2015BAD29B01) 中央高校基本科研业务费专项资金资助项目(CZP17007)
【分类号】：TP311.13;TS272.4
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本文编号：2092461