摘要
利用灰色系统理论是研究贫信息系统分析、建模、预测、决策、控制的有效工具的特性,针对系统样本数据量不大或有残缺,样本数据更新变换快,整体数据规律相当复杂,而在某一时间或空间的数据却有很强的规律性之类的贫信息灰色系统中的数据挖掘课题,探讨了灰色系统理论与技术在数据挖掘中的应用问题,提出了贫信息灰色数据挖掘的灰色关联算法、灰色统计算法、灰色聚类算法、灰色统计聚类算法,并提出了灰色系统数据挖掘的体系结构。
Grey system theory is an effective tool for system analysis, modeling, prediction decision making, and control on poor-information systems. This paper discusses the application of grey system theory to data mining in poor-information systems in which there is a little or non-complete samples, or sample data updates quickly, or whole sample data is very complex, but in some space or time region, sample data obeyes regularity. Some new algorithms, i.e. grey relational degree algorithm, grey statistics algorithm, grey clustering algorithm, and grey statistic clustering algorithm have been presented. And the system structure of grey data mining systems is constructed.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2004年第2期184-186,共3页
Systems Engineering and Electronics
基金
国家自然科学基金资助课题(79970025
69874018)
