摘要
粗糙集理论是一种新型的处理模糊和不确定知识的数学工具。目前已在人工智能、知识与数据发现、模式识别与分类、故障检测等方面得到了广泛应用。首先描述了粗糙集的基本算法及其复杂度,包括等价关系,上下近似及约简算法;然后对粗糙集在一些领域中的应用进展情况进行了论述,例如模式识别与人工神经元网络等,最后给出了建议的研究方向。
Rough set theory, a new mathematical tool that dealing with vagueness and uncertainty, was introduced by Pawlak in 1982. It has been widely used in the area of AI, data mining, pattern recognition, fault diagnostics etc. This paper describes the basic algorithms for rough set, including equivalent relation, upper/lower approximation and reduction. Then several extensions of rough set theory are diseussed such as pattern recognition, ANN etc. At last further research directions are discussed.
出处
《山西电子技术》
2006年第1期92-93,共2页
Shanxi Electronic Technology
关键词
粗糙集
知识发现
数据分析
rough set
knowledge discovery
data analysis
