【摘要】 针对某中药提取企业生产线采集的工艺控制数据以及产品质检数据利用K-means和DBSCAN聚类算法进行聚类,分别得到七个质检指标的聚类区间,为企业确定质检指标提供了科学的依据.还对Apriori算法进行了改进,在算法中加入了用户兴趣度的概念,控制了候选集指数增长,提高了运行速度.运用该算法发现了生产加工控制信息与产品质量指标之间的影响关系.更多还原

【Abstract】 K-means and DBSCAN clustering algorithm were used to cluster on the Chinese Medicine production line extraction of process control data collection as well as product quality data,respectively,seven quality control indicators have been clustering their interval,to identify quality control indicators for enterprises to provide a scientific basis.And Apriori algorithm was improved by adding a degree of the user interest in the concept,so the candidate set exponential growth was controlled,and the operating speed was increased.The relationship between production process control information and product quality indicators was found by using this algorithm.更多还原