摘要
对于生物化工产品的工业生产而言,更要有合适的生产环境条件,然而由于生产过程的复杂性,确定适宜的生产环境较为困难。就生化企业生产的数据特征,提出了生产数据的指标分割预处理及针对稀有数据的关联规则挖掘方法,对数据指标分割的过程进行了详细的阐述,并针对稀有数据挖掘,提出了关联规则挖掘中相对支持度的概念,在此基础上设计并开发生化企业关联规则挖掘数据分析系统,给出了系统的结构和功能,并对系统应用进行了试验和分析,取得了较好的效果。
Data Mining is a process of discovering knowledge or rules from available dataset. It is possible to make optimized production environment based on association rules mined from production data through association rule mining system. During the production process of Bio-chemical enterprises, it is expected that the environment such as temperature, water condition and raw material supply are appropriate to obtain best production output. However, due to the complexity of production, it is not easy to acquire the optimized condition. This paper therefore tries to design and develop a knowledge discovery software program intending to provide such tools. The paper also analyzes index segmentation and association rule mining from rare transactions from large dataset based on relative supporting value, which is illustrated in detail. The developed system was tested and verified in practice, which proves that the system can be applied in Bio-chemical production data analysis.
出处
《计算机系统应用》
2011年第9期7-11,共5页
Computer Systems & Applications
基金
国家自然科学基金(41071219)
蚌埠市企业节能增效项目(2007-10)
关键词
关联规则挖掘
知识发现
生化企业
知识挖掘系统
association rule mining
knowledge discovery
Bio-chemical enterprises
knowledge discovery system
