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.
In order to improve the efficiency of tea blending,saving the labor costs and achieving the maximum profit for tea enterprise,we model the problem of tea blending as the spatial clustering based on multi-dimensional hierarchy.We define the similarity measure criteria in multi-dimensional conceptual hierarchy space to improve k-medoids algorithm and solve the optimal blending scheme.By introducing Dewey coding,we improve the solving efficiency.The experiment on real life dataset shows that,compared with the manual way under the same experimental conditions,the intelligent tea blending scheme proposed in this paper has greatly improved the working efficiency and economic benefits for tea enterprises.
出处
《中南民族大学学报（自然科学版）》
CAS
北大核心
2017年第4期126-130,共5页
Journal of South-Central University for Nationalities：Natural Science Edition
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)
关键词
茶叶拼配
空间聚类
多维概念分层
DEWEY编码
k中心点算法
tea blending
spatial clustering
multi-dimensional conceptual hierarchy
Dewey coding
k-medoids algorithm
